Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving the registration process in a healthcare facility with lean principles

Purpose: Process improvement in service industries, like the registration process in a hospital, can be achieved with the application of lean principles. In this specific case, lean principles were essential to analyze and improve patient satisfaction in a hospital in Montana. The clinics involved in the study included pediatrics (P), internal medicine (IM), and cardiology/pulmonary (CP). The purpose of this study was to address difficulties regarding patient satisfaction on the registration and check-in processes. Design/methodology/approach: Direct observations and patient surveys were initially made to understand the processes and identify the initial causes of dissatisfaction. A value stream map (VSM) was then used to further break down the patient flow’s complexity. A Fishbone diagram and a Concept Map were completed to find the root of the dissatisfaction. Findings: The information obtained from the lean tools showed that patients questioned the need for having a central registration in combination with the check-in process when this combination generates duplications of steps that cause unwanted delays. Several recommendations were explored by the engineering team to mitigate these delays and improve the registration process reducing the number of patients complaints by 40%. Practical implications: This project illustrated the application of lean principles to resolve issues regarding a central registration format in a healthcare facility. Originality/value: A Concept Map was used as a tool to help the organization develop creative and new ways of looking at and solving process deficiencies.
Innovation Diffusion Impact on Students’ Online Platform Participation

Journal of Entrepreneurship and Business 118 Abstract – Technology and innovation offer excellent opportunities for educational institutions, particularly Higher Education Institutions (HEIs), to provide high-quality education services in the industry 4.0 era. Most classes are conducted online during the pandemic, whereby students fully participate in online learning activities and processes. Thus, the study aims to examine the influence of relative advantage, complexity, and observability on students’ online platform participation. The study employed a cross-sectional research design and collected quantitative data from 384 students using a purposive sampling technique. Additionally, a questionnaire was distributed through WhatsApp and Facebook to collect data and analysed using the statistical package for social sciences (SPSS) version 21. The findings revealed that relative advantage, complexity, and observability significantly affect students’ online platform participation. Furthermore, the study provided several insights into students’ online participation.
Physicochemical Characteristics of Chicken Eggshell Flour Produced by Hydrochloric Acid and Acetic Acid Extraction

BACKGROUND: Several previous researchers have prepared chicken eggshell flour using hydrochloric acid (HCl) and acetic acid (CH3COOH) solvents. However, the results of the physicochemical characteristics still very diverse. AIM: This study aims to produce chicken eggshell flour using two different types of solvents (4% HCl and CH3COOH 2N) and determine the proper solvent to obtain better physicochemical characteristics. METHODS: This type of research was descriptive quantitative. The research stages initiated by preparing chicken eggshell samples by maceration using 4% HCl and CH3COOH 2N. Afterward, chemical characteristics (moisture content, ash, calcium carbonate, calcium, and phosphorus) and physical characteristics (yield) of eggshell flour were determined. Processing and data conducted using the IBM SPSS statistic program. RESULTS: The higher levels of calcium, calcium carbonate, phosphorus, ash, yield, and lower water content of the eggshell powder were generated by extraction using 4% HCl than 2N acetic acid (CH3COOH). CONCLUSION: The physicochemical characteristics of the eggshell powder extracted from the 4% HCl were better than the 2N acetic acid (CH3COOH). Edited by: Slavica Hristomanova-Mitkovska Citation: Rosnah R, Taslim NA, Aman AM, Idris I, As’ad S, Bukhari A, Wahyudin E. Physicochemical Characteristics of Chicken Eggshell Flour Produced by Hydrochloric Acid (HCl) and Acetic Acid (CH3COOH) Extraction. Open Access Maced J Med Sci. 2021 Jun 26; 9(A):428-432. https://doi.org/10.3889/oamjms.2021. 6238
STUDY OF EMOTIONAL INTELLIGENCE AMONG UNIVERSITY STUDENTS: TECHNICAL COMPETENCE

The artificial intelligence (AI) system related research and concepts are changing with rapid pace and are becoming more and more important and relevant to the present needs. The concept of emotional intelligence is one of the primary concern for AI research. The interaction with human emotions intelligently is the need of the hour for the technology. The integration of AI with emotional intelligence systems should work along with humans. Emotions in humans is a multidimensional parameter and therefore could not be considered as a mechanism for enhancing intelligence. We have studied the emotional intelligence among the university students of different School of Studies. The issues related to technical competence have been discussed. A sample of 100 students (70 males and 30 females) drawn from 6 School of Studies has been considered. A questionnaire consisting of 16 questions was prepared and mailed to the students. The data collected was analysed. We observed that under the category of reading people, all the four variants namely self-analysis, analysis of others, self-expression and discrimination, the emotional intelligence is very high, more than 70%. All the four variants under the category using emotions, the emotional intelligence is very high, more than 80%. In case of judgement, the emotional intelligence was extremely high (90%). The three variants under the category understanding emotions, the emotional intelligence is very high, more than 80%. The three variants under the category managing emotions, the emotional intelligence is very high, more than 70%. In case of self-control, the emotional intelligence was extremely high (90%).
Climate Change and (a Culture of) Cooperation in the World's Most Agricultural Countries.

Overwhelming evidence suggests that a “culture of cooperation,” which is the implicit reward from cooperating in any economic activity, represents one of the most successful humanly devised social structures. Yet, our understanding of its determinants and impact is still limited. To clarify these issues, we propose a time inconsistency theory of state-building and we document that, in the world's most agricultural countries, adverse climate shocks push the nonelites to accumulate strong norms of cooperation. To illustrate, a strong culture signals the nonelites’ commitment to cooperate with the elites in joint investment activities despite the small expected payoff and encourages the elites to reciprocate by granting a more inclusive political process. These reforms, in turn, help convince the nonelites that a sufficient part of the investment returns will be shared via public good provision. Our estimates imply that the severity of droughts has two short run effects on agricultural output, a negative impact due to worse farming conditions and a positive effect due to stronger norms of trust and respect. Accordingly, policymakers should consider the direct and indirect impacts of climate change and favor endogenous cultural formation. Moreover, environmental policies should be designed through a more credible interdisciplinary approach.
Repositioning students as co-creators of curriculum for online learning resources

Amid increasing calls for universities to transition to online learning, there is a need to explore how platforms and technology can provide positive student experiences and support learning. In this paper, we discuss the implementation of an online peer learning and recommender platform in a large, multi-campus, first-year health subject (n = 2095). The Recommendation in Personalised Peer Learning Environments (RiPPLE) platform supports student’s co-creation of learning resources and allows for students to provide feedback and rate their peers’ submissions. Our results indicated that both student engagement and academic performance were positively impacted for users by the introduction of the RiPPLE platform, but that academic preparedness, in the form of students’ ATAR scores, strongly influenced their engagement and the benefits received.
The impact of human resources (HR) activities on competitive advantage in private schools in Jordan: A case study

The aim of this study was to identify the impact of HR activities on competitive advantage in private schools. The study uses primary data collected with the help of well-structured questionnaire that was developed and distributed among a sample of 92 respondents (49 female and 43 male), questionnaire results were statistically analyzed to test the hypotheses that were developed to identify the impact of HR activities on competitive advantages. Multiple regression analysis was used as a statistical tool and technique to identify five key elements: recruitment and reward system, training and skill development activities, organization climate, employee participation and empowerment; and effective communication system to determine competitive advantage in private schools in Jordan. The results indicated that there is a statistically significant effect of HR activities on the competitive advantage; On the other hand, there is no impact of other variables. © 2021 by the authors. Licensee SSBFNET, Istanbul, Turkey. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Gender Differences in Absolute and Relative Values of Hand Dynamometer Test with 9 and 10-Year Old Children From the Skopje Region in R.N. Macedonia

Background. Handgrip strength test is applied both to adults and children to indicate muscular fitness as well as the nutritional and health status. It differs in adults and adolescents depending on the gender. However, it is not clear whether a difference exists also in children at 9 to 10 years of age, and what are the factors that influence it. The goal of the research was to determine the absolute and relative values of the hand dynamometer test with healthy Macedonian boys and girls aged 9 and 10 from the Skopje region as well as to determine the factors that affect the handgrip strength at that age. Materials and methods. The research was conducted on a sample of 775 children (boys n = 386; girls n = 389), whereby the following characteristics were measured: handgrip strength, weight, height, body fat percentage, muscle mass percentage and the body mass index (BMI) was calculated. The maximum handgrip strength was measured with a digital Takei TKK 5101 dynamometer. Results. The research found that there are statistically significant differences in the absolute values obtained in the hand dynamometer test between healthy boys and girls in Macedonia at 9 and 10 years of age. On the basis of the results obtained from the research, one can conclude that the results of the hand dynamometer test are affected by age, gender and body composition. Conclusion. Based on the increasing predominance of children’s obesity, the present study can provide clinicians and researchers with an insight how body composition influences muscular fitness, and can serve policy-makers to develop gender-specific strategies about body-weight management and promotion of muscular performance among children and adolescents.
Do Corporate Social Responsibility and Investor Protection Limit Earnings Management? Evidence from Indonesia and Malaysia

Research aims: This study aims to investigate the effect of corporate social responsibility on earnings management by considering the impact of investor protection.Design/Methodology/Approach: This study’s population was plantation companies listed in Indonesia Stock Exchange and Malaysia Stock Exchange. The period of this study was from 2012 to 2017. Moreover, the hypotheses testing technique used was multiple regression analysis.Research findings: This study’s results revealed that corporate social responsibility disclosure and investor protection significantly affected earnings management.Theoretical contribution/Originality: These results support the ethics hypothesis stating that companies committed to ethics view earnings management unethical behavior. This study also verifies the relationship between legal systems and earnings management.
Application of tot’hema eosin sensitized gelatin film for adaptive microlenses

BRANKA D. MURIĆ, University of Belgrade, Original scientific paper Institute of Physics, Belgrade UDC: 617.7-76 DEJAN V. PANTELIĆ, University of Belgrade, DOI: 10.5937/tehnika1706787M Institute of Physics, Belgrade DARKO M. VASILJEVIĆ, University of Belgrade, Institute of Physics, Belgrade SVETLANA N. SAVIĆ-ŠEVIĆ, University of Belgrade, Institute of Physics, Belgrade BRANISLAV M. JELENKOVIĆ, University of Belgrade, Institute of Physics, Belgrade
EXAFS Debye-Waller Factors of B2-FeAl Alloys

This work develops the anharmonic correlated Debye model to study the temperaturedependent extended X-ray absorption fine structure (EXAFS) Debye-Waller factors (DWFs) of B2FeAl alloys. We derived the analytical expressions of the EXAFS DWF and Debye frequency as functions of temperature. Numerical calculations were performed for Fe1-yAly alloys with various Al concentration (y = 0.35, 0.40, 0.45 and 0.50) in which Fe-Al alloys still maintained B2 structure. The good agreement between our theoretical results with previous data verifies our developed theory. Our calculations show that DWFs of Fe1-yAly alloys increase robustly when temperature and/or Al concentration in Fe1-yAly alloys increase. The increasing of DWF will cause the reduction of the amplitude of EXAFS.
Outage Analysis in SWIPT-Based Decode-and-Forward Relay Networks with Partial Relay Selection

Faculty of Electronics Technology, Industrial University of Ho Chi Minh City, Ho Chi Minh City, Vietnam Faculty of Automobile Technology, Van Lang University, Ho Chi Minh City, Vietnam Department of Computer Fundamentals, FPT University, Ho Chi Minh City, Vietnam Faculty of Information Technology, Ho Chi Minh City University of Food Industry, Ho Chi Minh City, Vietnam Modeling Evolutionary Algorithms Simulation and Artificial Intelligence, Faculty of Electrical & Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam Wireless Communications Research Group, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam
MONITORING TERRAIN DEFORMATIONS CAUSED BY UNDERGROUND MINING USING UAV DATA

Underground mining causes terrain surface deformations that lead to various threats to the environment and people, thus a systematic deformation monitoring needs to be performed. This monitoring mainly focuses only on the vertical part of the deformation and remote sensing techniques are currently very often used for this purpose. The development of Unmanned Aerial Systems (UASs) open new possibilities in this context. Most commonly, the mapping UASs are equipped with RGB cameras but also other lightweight sensors are utilized. In this work, the usefulness of UAS photogrammetry and LiDAR data is investigated in the context of detection and measurement of terrain deformations caused by underground mining. The accuracy of the methods was compared in reference to TLS data. The UAS and TLS measurements were performed in 2018 and 2019 but the subsidence was also evaluated in regards to ALS data acquired in 2011. The standard methodology based on Digital Terrain Models of Difference (DoDs) was applied to detect the subsidence. The DoD analysis was restricted to the hard surfaces. The profiles along the roads were also analysed to validate the accuracy of the data. The analysis showed that the UAS photogrammetry enables to obtain less noisy data and more accurate results of the terrain subsidence measurement than the UAS LiDAR sensors. The comparison of the DoDs showed about 33 cm subsidence between 2011 and 2018, which gives a subsidence rate of about 5 cm/year. The observed subsidence between years 2018 and 2019 was equal to about 5 to 15 cm depending on the measurement technique and investigated area.
Resonant Moments in Media Events:

Live-tweeting has emerged as a popular hybrid media activity during broadcasted media events. Through second screens, users are able to engage with one another and react in real time to the broadcasted content. These reactions are dynamic: they ebb and flow throughout the media event as users respond to and converse about different memorable moments. Using the first 2016 U.S. presidential debate between Hillary Clinton and Donald Trump as a case, this paper employs a temporal method for identifying resonant moments on social media during televised events by combining time series analysis, qualitative (human-in-the-loop) evaluation, and a novel natural language processing tool to identify discursive shifts before and after resonant moments. This analysis finds key differences in social media discourse about the two candidates. Notably, Trump received substantially more coverage than Clinton throughout the debate. However, a more in-depth analysis of these candidates’ resonant moments reveals that discourse about Trump tended to be more critical compared to discourse associated with Clinton’s resonant moments.
Effect of adjuvant yoga therapy on stress, anxiety, and depression in participants of an alcohol de- addiction program

Introduction: Alcohol-related disorders have disrupted the everyday life of the consumer gradually and led to a rise in alcohol-related diseases, violence, including homicide, suicide, sexual assault, and intimate partner violence. Long-term diseases, such as high blood pressure, heart disease, stroke, liver disease, and digestive problems are also rising due to excessive alcohol intake. Moreover, social problems, including lost productivity, family problems, unemployment are due to excessive alcohol intake. Aim: To study the effects of adjuvant yoga therapy on stress, anxiety, and depression in patients undergoing an alcohol de-addiction program at de-addiction clinic, department of Psychiatry, Mahatma Gandhi Medical College & Research Institute (MGMC&RI) in Pondicherry. Settings and design: Seventy-one male patients undergoing an alcohol de-addiction program were recruited as subjects and randomly divided into Group A, who received Yoga therapy as per the CYTER protocol, daily counseling, warm-ups (Jathis) along with standard medication for minimum 6-7 sessions of 1 to 1.5 hours each session, and Group B, who only received standard medical management. Methods and materials: The patients were administered the Perceived Stress Scale (PSS) and Hospital Anxiety & Depression Scale (HADS) before and after the intervention. Statistical analysis used: Statistical analysis was carried out using JASP-0.9. 2.0 software. Wilcoxon test was performed for intragroup comparisons, and the Mann-Whitney test was performed for intergroup comparison to arrive at the p values. Results: The intervention group showed significant changes in stress (p=0.0319), anxiety (p=0.0040), and depression (p=0.0571) in the intergroup comparisons, i.e., with the control group. In the intragroup comparisons, i.e., within the intervention group, stress (p<0.001), anxiety (p<0.001), and depression (p<0.01) showed significant changes as well. Conclusion: The present study supports previous studies on the benefits of Yoga and concludes that yoga therapy helps in managing stress, anxiety, and depression levels of patients of Alcohol Dependence Syndrome (ADS). www.ijcrt. org © 2020 IJCRT | Volume 8, Issue 12 December 2020 | ISSN: 2320-2882 IJCRT2012217 International Journal of Creative Research Thoughts (IJCRT) www.ijcrt. org 2094
MrSQM: Fast Time Series Classification with Symbolic Representations

Symbolic representations of time series have proven to be effective for time series classification, with many recent approaches including BOSS, WEASEL, and MrSEQL. The key idea is to transform numerical time series to symbolic representations in the time or frequency domain, i.e., sequences of symbols, and then extract features from these sequences. While achieving high accuracy, existing symbolic classifiers are computationally expensive. It is also not clear whether further accuracy and speed improvements could be gained by a careful analysis of the symbolic transform and the trade-offs between time domain and frequency domain symbolic features. In this paper we present MrSQM, a new time series classifier that uses multiple symbolic representations and efficient sequence mining, to extract important time series features. We study two symbolic transforms and four feature selection approaches on symbolic sequences, ranging from fully supervised, to unsupervised and hybrids. We propose a new approach for optimal supervised symbolic feature selection in all-subsequence space, by adapting a Chi-squared bound developed for discriminative pattern mining, to time series. Our experiments on the 112 datasets of the UEA/UCR benchmark demonstrate that MrSQM can quickly extract useful features and learn accurate classifiers with the logistic regression algorithm. We show that a fast symbolic transform combined with a simple feature selection strategy can be highly effective as compared to more sophisticated and expensive feature selection methods. MrSQM completes training and prediction on 112 UEA/UCR datasets in 1.5h for an accuracy comparable to existing efficient state-of-the-art methods, e.g., MrSEQL (10h) and ROCKET (2.5h). Furthermore, MrSQM enables the user to trade-off accuracy and speed by controlling the type and number of symbolic representations, thus further reducing the total runtime to 20 minutes for a similar level of accuracy. Thach Le Nguyen and Georgiana Ifrim are with the School of Computer Science, Insight Centre for Data Analytics, University College Dublin, Ireland. {thach.lenguyen, georgiana.ifrim}@ucd.ie ar X iv :2 10 9. 01 03 6v 2 [ cs . L G ] 1 4 M ar 2 02 2 2 Thach Le Nguyen, Georgiana Ifrim
Relationship between requirements analyzability, interpersonal trust, and software project performance: Moderating role of customization

Based on the information processing perspective, this study empirically investigated the effects of requirements analyzability, an indicator of technological complexity and interpersonal trust as the soft factor of buyer-supplier relationships on software project development performance. Beyond that, the possible moderator role of the degree of software customization was examined on the analyzabilityinterpersonal trust and analyzability-performance links. Data were collected from 138 companies through a questionnaire-based survey of IT purchasing managers in Turkey. Partial Least Squares Structural Equation Modeling was used to test the research hypotheses. This study indicated that requirements analyzability and interpersonal trust have a significant effect on software performance. Overall, the study provides evidence that interpersonal trust mediates the relationship between requirements analyzability and software project performance. The research findings support the moderation role of customization in the relationship between requirements analyzability and software project performance. However, partial support is provided for the moderating effect of customization on the relationship between requirements analyzability and interpersonal trust.