Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of Soft Computing Techniques for the Analysis of Tractive Properties of a Low-Power Agricultural Tractor under Various Soil Conditions

Considering the fuel consumption and soil compaction, optimization of the performance of tractors is crucial for modern agricultural practices. The tractive performance is influenced by many factors, making it difficult to be modeled. In this work, the traction force and tractive efficiency of a low-power tractor, as affected by soil coefficient, vertical load, horizontal deformation, soil compaction, and soil moisture, were studied. The optimal work of a tractor is a compromise between the maximum traction force and the maximum tractive efficiency. Optimizing these factors is complex and requires accurate models. To this end, the performances of soft computing approaches, including neural networks, genetic algorithms, and adaptive network fuzzy inference system, were evaluated. The optimal performance was realized by neural networks trained by backpropagation as well as backpropagation combined with a genetic algorithm, with a coefficient of determination of 0.955 for the traction force and 0.954 for the tractive efficiency. Based on models with the best accuracy, a sensitivity analysis was performed. The results showed that the traction performance is mainly influenced by the soil type; nevertheless, the vertical load and soil moisture also exhibited a relatively strong influence.
Fostering Empathic Skills in Mainstream Public School Pupils: Efficacy Assessment of the EPaN Empathy Training Program

Empathic skills are called for in every social interaction, but there are few evidence-based programs in the mainstream public school sector exclusively dedicated to fostering the empathic sub-components of recognition of emotions, emotional perspective taking and affective responsiveness in pupils. The EPaN program is based on the latest scientific knowledge and best practices that can be taught in the classroom. In the course of eight school weeks, using a pre-post-test design we studied the effectiveness of an empathy training program ( EPaN ) in nine classes with a total of 123 mainstream public school pupils aged 11.2 to 15.2 years, divided into intervention groups that were assigned a total of 24 exercises of 15 to 40 minutes duration and control groups that followed the regular lesson plan. After the training, variance analysis showed a significant improvement in the empathic sub-capacities for recognition of emotion , emotional perspective taking and affective responsiveness in the intervention groups compared to the control groups. These results are examined in light of their importance and adaptability of the EPaN program to educational practice.
Learning-based approaches for feature fusion in multi-modal indoor localization

Due to their aptitude in capturing complex dependencies, neural networks are a promising candidate for indoor localization. Omnipresent phenomena such as multi-path signal propagation, shadowing and device noise introduce non-linear effects in the data, and make conventional geometry-based methods fail even in simple environments. This semester project explores few analytical outliers rejection algorithm and new fusion methods based on neural networks and compares them with an analytical model.
USING A CASE-BASED REASONING APPROACH IN ON-LINE LEARNING: IN LEARNING ABOUT RURAL PRACTICE

This paper describes the early work undertaken in the design, and implementation of an on-line learning environment created for the Master of Rural Health (MRH) program at the University of South Australia using a Case-Based Reasoning approach. Utilising the UniSAnet version2 platform a template for the MRH program was created. The Master of Rural Health program primarily caters for the professional needs of health and human service personnel who are living and working in rural Australia. The content of this program reflects contemporary issues in health and human services where learners have the opportunity to hone their skills in managing human, IT as well as other resources vital for effective practice and functioning in health related organizations. Many professionals find rural practice to be isolating and for this reason we adopted a Case-Based Reasoning (CBR) approach as the conceptual framework for the courses offered in this new program enabling practitioners to interact, react and learn from a repository of expert cases that is made available on-line. The discussion gives insight to life and work in rural communities and the learner experience in the course entitled ‘Practice in Rural Communities’.
An all-digital ΣΔ--frequency discriminator of arbitrary order

-In this paper, we propose an all-digital frequency output of the synthesizer. High reference frequency (REF) is synthesizer architecture, based on an all-digital XA-frequency used to push the spurs far from the carrier. The need for high discriminator. The new all-digital synthesizer is compared to sampling frequency, in addition to the resolution being previously published work. The architecture of the XA-dependent on the number of stages, both make the TDC frequency discriminator is verified using behavioral power hungry. In this work, we show that using XA-noise simulation. shaping techniques, we can avoid the use of a TDC and implement an all-digital noise-shaped frequency
xCoAx 2019: Some Things You Can Ask Me

This paper explores the relationship between gender and artificial intelligence, drawing on an analysis of digital assistants that reveals how these entities tend to be feminized through their anthropomorphization, the tasks they perform, and their behavioral traits. Furthering this discussion, it focuses on the main questions raised by researchers and academics when examining the feminization of artificial intelligence. It then confronts these views with current discourses on the phenomenon in the context of online media coverage, while also considering how AI is portrayed in popular culture and bodies of fiction. Finally, it observes current trends of development of digital assistants, such as Alexa, Cortana, Google Assistant or Siri, and their stance towards gender according to the functions or features they prioritize. In this manner, this study seeks to promote discussion and tackle the questions that arise when the relationship between gender and AI is subject to closer inspection.
The Quest to Provide a Complete Personal Health Record

This annotated bibliography examines the social, technical, and regulatory challenges of providing patients and care teams with complete personal health records. The intended audience includes executives, policy makers, and product developers within the healthcare service and technology industries. Scholarly literature published between 2015 and 2019 was referenced to identify challenges and possible solutions for integrating health and wellness data from multiple sources and devices in order to create longitudinal personal health records.
Overview of the Advancements in Automatic Emotion Recognition: Comparative Performance of Commercial Algorithms

In the recent years facial emotion recognition algorithms have evolved and in some cases top commercial algorithms detect emotions like happiness better than humans do. To evaluate the performance of these algorithms, the common practice is to compare them with human-labeled ground truth. This article covers monitoring of the advancements in automatic emotion recognition solutions, and here we suggest an additional criteria for their evaluation, that is the agreement between algorithms’ predictions. In this work, we compare the performance of four commercial algorithms: Affectiva Affdex, Microsoft Cognitive Services Face module Emotion Recognition, Amazon Rekognition Face Analysis, and Neurodata Lab Emotion Recognition on three datasets AFEW, RAVDESS, and SAVEE, that differ in terms of control over conditions of data acquisition. We assume that the consistency among algorithms’ predictions indicates the reliability of the predicted emotion. Overall results show that the algorithms with higher accuracy and f1-scores that were obtained for human-labeled ground truth (Microsoft’s, Neurodata Lab’s, and Amazon’s), showed higher agreement between their predictions. Agreement among algorithms’ predictions is a promising criteria in terms of further exploring the option to replace human data labeling with automatic annotation.
A non-parametric approach for exploring bank proficiency. A case of indian nationalized banks

The main purpose of the study is to examine the relative efficiency of the Indian Nationalized Banks and also to analyse the efficiency and profitability connexion. This paper is unique in the sense that it analyses the banks by using the Non-parametric methods. This piece of work classified the banks in terms of efficient and inefficient which may help the banks to take remedial measures in order to improve the efficiency and profitability. With a view to cultivate a base for performance appraisal and relate it to nationalized banks in India, Data Envelopment Analysis (DEA) and Free Disposal Hull (FDH) programming mathematical models are used to assess the financial performance of the banks in India.
English as a Lingua Franca for EFL Contexts

English as a Lingua Franca for EFL Contexts is an innovative book containing a compendium of chapters on the implementation of the notion of English as a Lingua Franca (ELF) in the English as a Foreign Language (EFL) classroom. In other words, it suggests an ELF-aware approach to English language teaching. The book starts with an introduction by the editors (Nicos Sifakis and Natasha Tsantila) in which they set the grounds for the concepts of ELF and EFL from a critical perspective. This introduction includes a brief theoretical review of the topic and also reflects on the implications of ELF research for language teaching and its connections with EFL practice.
Correlation between dimensions of psychological well-being with life satisfaction and self-regulation

Introduction: The purpose of this study was to investigate the effect of psychological well-being’s dimensions on the life satisfaction and self-regulation in employees of Zahedan city. Materials and Methods: In this descriptive-correlational study, 500 employees of university were selected randomly. Research instrument included: Reef’s Psychological Well-being Questionnaire (18 questions), Life Satisfaction Questionnaire (5 questions) and Miller and Brown Self-Regulatory Inventory. Data analyzed through descriptive statistics, Pearson correlation, stepwise regression and SPSS version 24. Results: The results indicated that five dimensions of psychological well-being had a positive significant relationship with life satisfaction at 99% level. Meanwhile, self-regulation was related to self-control, autonomy, positive relationships significantly. The positive relationship with others, personal growth, independence, self-acceptance and environmental domination explained 6.49%, 6.13%, 5.91%, 5.78%, and 5.74% of variance for life satisfaction. Also, independence explained 21.31% of variance for self-regulation. Conclusion: It seems that dimensions of psychological well-being are effective on life satisfaction and selfregulation. Educational programs about psychological well-being should be used with providing conditions and facilities for increasing employees’ life satisfaction and self-regulation.
Effect of Auditor Independence, Fee Audit, Audit Tenure Toward Audit Quality (Case Study at a Public Accounting Firm in Bali)

This study aims to examine: (1) the effect of the influence of auditor independence on audit quality, (2) the effect of audit fees on audit quality, (3) the effect of audit tenure on audit quality. The type of data used is questionnaire. The population in this study are all auditors who work at the Public Accounting Firm in Bali. Determination of the sample is done using simple random sampling and which can be analyzed as many as 87 respondents. Data analysis was performed by multiple regression analysis. The test results show that (1) auditor independence has a significant effect on audit quality, (2) audit fees have a significant effect on audit quality, (3) audit tenure has no significant effect on audit quality.
The Relationship Between Motivation Extrinsic and Intrinsic, Mother Tongue and Chinese Proficiency Among Preservice Teachers

Chinese language proficiency is an indicator of language performance for every preservice Chinese teacher. This study examines the relationship between extrinsic and intrinsic motivation, mother tongue, and Chinese language proficiency. Data was collected using the survey method that employed selfdetermination questionnaires and a Chinese language proficiency test. The sample consisted of 407 preservice teachers (Chinese=275, Malay=132) from five Malaysia Teacher Training Institutes who were pursuing a Chinese language teaching course. The Smart PLS path model analysis revealed three important findings. Firstly, the relationship between intrinsic motivation and Chinese language proficiency was significantly related. Secondly, the relationship between extrinsic motivation and Chinese language proficiency was significantly negatively related. Thirdly, mother tongue did not significantly influence the relationship between self-determination and Chinese language proficiency among Chinese preservice teachers. This study can help to plan teacher training educational programs that would encourage more people to pursue Chinese language studies.
To Study Relationship between the Dimensions of Service Quality and Customer Satisfaction, Customer Loyalty and Customer Switchover Intention of Public Sector Banks

The article tries to find out the “relationship between the dimensions of service quality and, customer satisfaction, customer loyalty and customer switchover intention of public sector banks” is undertaken among the customers who maintain relationship with the public sector banks in the Salem district at different geographic locations namely, rural, semi-urban, and urban where different customers are studied. Service Quality has significant correlation at the 0.01 level with the other factors variables namely, Customer Satisfaction (r = 0.673), Customer Loyalty (r = 0.565), Customer Switchover Intention (r = 0.441). From this result it is very clear that Service Quality has higher and significant correlation with Customer Satisfaction and Customer Loyalty than Customer Switchover Intention. It is also found that Customers have more satisfaction with the present banking service quality. Hence, it is concluded that Customer Switchover Intention has significant lower correlation with banking service quality, customer satisfaction and loyalty. Retaining of existing customers and capturing the new customers is a challenging task for the bank managers. Therefore, bank managers should regularly monitor employees’ skills, efficiency and dealing with customers and should confirm whether all business transactions are made with ethical procedures.
Review of Patient Satisfaction Research to Improve Patient Surveys in Medical Imaging Departments

Patient satisfaction is important to health care facilities because a satisfied customer tends to return for additional services. Identifying the characteristics that increase patient satisfaction can help facilities improve their process. Few studies have directly evaluated imaging departments, but the literature from other health care specialties can be applied when the environment is similar. Having a pleasant waiting experience has shown to have a positive impact on patients’ overall satisfaction and perceived quality of care. Factors that have been linked to improved patient satisfaction include decreased wait time, decreased perceived length of wait time, and increased communication through written information or increased face-to-face time with a provider.
Improving quality of livestock products to meet market and community demands

The Australian sheep industry, particularly the lamb meat sector has undergone a major change in focus, such that consumer requirements are a paramount determinant for production and processing developments. This change has been facilitated by the use of cross breeding production systems where the benefits of heterosis are captured and the implementation of a performance recording system amongst initially, breeders of terminal sires. This sector of the industry has strongly embraced genetic selection using objectively measured traits and this is one of the contributors to the superior growth rate of crossbred progeny over pure bred progeny. A crossbreeding system does present challenges as it can also lead to fatter carcases depending on slaughter weight targets and thus less lean or saleable meat. This means that appropriate sire selection is mandatory. Which ever region of the world is under consideration; crossbreeding for meat production will return benefits and these will be further strengthened if the processing sector also adopts technology to enhance eating quality such as electrical stimulation and ageing.
Asymmetric effects of exchange rate changes on the demand for divisia money in Malaysia

Financial liberalisation has advanced the transformation of the financial market as more interest-bearing financial derivatives are introduced. Performance of the equal-weighted monetary aggregates has been affected and therefore disrupted the stability of money demand. Effectiveness of monetary policy is a concern as stability of money demand is required for a stable velocity derivation. Thus, the aim of this study is to derive a stable money demand function by considering the type of monetary aggregate included for estimation and the missing determinants of money demand. First, the divisia monetary aggregate is employed for money demand estimation in Malaysia. Second, the exchange rate is included as a determinant of money demand by employing the nonlinear autoregressive distributed lag approach to capture the asymmetric effects from exchange rate changes. The results indicate that all the variables are bound together in the long run and the model is stable. Asymmetric effects exist in the short run for both appreciation and depreciation. Long-run asymmetric effects only hold in currency appreciation in which a substitution effect exists between Received: December, 2018 1st Revision: February, 2019 Accepted: October, 2019 DOI: 10.14254/20718330.2019/12-4/4 Journal of International Studies S ci en ti fi c P a pe rs © Foundation of International Studies, 2019 © CSR, 2019 Choi-Meng Leong, Chin-Hong Puah, Evan Lau, Abu Mansor Shazali Asymmetric effects of exchange rate changes on the demand for divisia money in Malaysia 53 exchange rate and money demand. A stable money demand function contributes to formulation of monetary policy in Malaysia.
Hierarchical and Complex ZnO Nanostructures by Microwave-Assisted Synthesis: Morphologies, Growth Mechanism and Classification

Zinc Oxide is an important and multi-purpose material in various industries due to its particular chemical and physical properties. Discovering a cheap, fast, clean, safe, and easy to use method, to synthesize this oxide nanoparticle has attracted a lot of attention in recent applications. The unique properties of the microwave and its special heating capabilities have yielded desirable outcomes by combining different synthesis methods. In the recent years, the vast majority of studies focus on the microwave-assisted synthesis of zinc oxide nanoparticles. This review article attempts to go over the recent advancements on the synthesis of zinc oxide nanoparticles with the aid of microwave, different morphologies and applications obtained by this method. Various microwave-assisted synthesis methods are classified, including the solution-based methods such as hydrothermal, solgel, and combustion methods. Morphology of the nanoparticles can affect the properties, and subsequently, applications of these nanoparticles. On the other hand, there is great diversity of morphological and synthesis conditions of zinc oxide nanoparticles. Thus, categorizing the synthesis techniques and providing features of them, facilitates the selection of appropriate method for designing new hierarchical structures with potential properties for future applications. Also it is endeavored to focus on the formation mechanisms of these methods. Finally, the various morphologies obtained under microwave radiation and their formation mechanisms are discussed and the effective factors in the synthesis are analyzed and presented. The potential and suitable fields of development and progress in the future studies are also proposed. Abbreviations: ACAC 2000, Acetyl Acetate 2000; CTAB, Cetyl Trimethyl Ammonium Bromide; DDA, Do Decyl Amine; EDA, Ethylene Di Amine; EG, Ethylene Glycol; HMT, Hexa Methylene Tetramine; LCS, Low-temperature Combustion Synthesis; PEG 400, Poly Ethylene Glycol 400; PS, Precursor Solution; PVA, Poly Vinyl Alcohol; PVP, Poly Vinyl Pyrrolidone; SCS, Solution Combustion Synthesis; SDS, Sodium Dodecyl Sulfate; SHS, Selfpropagation High-temperature Synthesis; SSGC, Synthesis by Sol-Gel Combustion; TEA, Tri Ethanol Amine; VCS, Volume Combustion Synthesis
Comparison of cytotoxic effects of calcium silicate-based materials on human pulp fibroblasts Mehmet

Background. This study aimed to compare the in vitro cytotoxicity of Theracal LC, BiodentineTM, iRoot BP Plus, and MTA Angelus on human pulp fibroblasts (HPF). Methods. Fifteen discs from each calcium silicate-based material were prepared in sterile Teflon molds. After setting, the fabricated discs were eluated with a culture medium for 24 h. HPF cells were plated onto 24-well plates at 5×103 cells/well, and the cells were exposed to the material eluates. The cell viability was evaluated with MTT assay at three different times (24, 48, and 72 h). Data were statistically analyzed. The apoptotic/necrotic status of HPF cells exposed to material eluates was determined by flow cytometry. Results. The differences between the effects of Theracal LC, BiodentineTM, MTA Angelus, and iRoot BP Plus on HPF cells were found to be statistically significant (P<0.05). Theracal LC was found to be more cytotoxic considering other vital pulp capping materials at 24- (28.3%), 48- (44.9%), and 72-hour (49.2%) intervals. On the other hand, BiodentineTM showed the least cytotoxic effects (97.1%, 130.0%, and 103.7%, respectively) According to flow cytometry results, Theracal LC material increased apoptosis/necrosis ratios compared to the other materials. Conclusion. Based on the results of the present study, BiodentineTM, MTA Angelus, and iRoot BP Plus can be classified as biocompatible materials in vital endodontic treatments. However, the Theracal LC materials should be used carefully due to their cytotoxic effects.
Dynamic filtering of malicious records using machine learning integrated databases

Machine Learning, Deep Learning and Predictive Analytics are the key domains of research in assorted domains of implementations including engineering, finance, economics, real time imaging and many others. The researchers are working on different tools and technologies including open source and own developed frameworks so that the higher degree of accuracy can be achieved. The research reports from Market Research News US predicted that the global market size of machine learning based implementations will exceed 20 billion dollars in year 2024. Most of the government and social services are nowadays in process to be deployed with the advanced technologies of machine learning and deep learning so that the minimum error factor can be there. The key players in the industry include; Google, Facebook, IBM Watson, Baidu, Apple, Microsoft, Wipro, Amazon, Intel, Nuance and many others which are working on the advanced algorithms and implementation perspectives of machine learning.