bluuebunny/crossref_metadata_2025_split huggingface dataset:
Decadal Remote Sensing Analysis of Seagrass Changes in Palu Bay, Central Sulawesi
Authors: Tis'in Musayyadah , Ambo-Rappe Rohani , Supriadi Supriadi , Faizal Ahmad 
Published: August 2023

Seagrass meadows provide a variety of material, non-material and regulatory coastal ecosystem service; however, as the distribution of seagrass beds changes over time due to both anthropogenic activities and natural factors, it is important to monitor changes in seagrass condition. Seagrass meadows in Palu Bay are threatened by activities such as coastal development and land reclamation. Additionally, the bay was hit by a significant tsunami in 2018, which could have impacted ecosystems in the bay, including seagrass meadows. The aim of this study was to detect changes in seagrass extent and distribution over a 10-year period from 2012 to 2022 and changes in land use over approximately a decade (2010 and 2021) through the use of remote sensing technology. Changes in eagrass meadow areal extent were analyzed using data from a 2012 Landsat 7 Satellite Data Acquisition and a 2022 Landsat 8 Satellite Data Acquisition. Water column correction was implemented using the Lyzenga Algorithm. The results showed a significant decrease in the area of seagrass meadows around the coastal area of Palu Bay. Seagrass meadows in 2012 and 2022 covered 127.08 Ha and 87.79 Ha, respectively, indicating a decrease in extent of 43.29 Ha. As the accuracy of the satellite data classification results was 80%, the results are considered acceptable. Anthropogenic activities (mainly mining and construction related) are strongly suspected as the main drivers of this decline, while earthquake and tsunami events likely aggravated the degradation of coastal ecosystems in Palu Bay, including seagrass meadows.
Accounting Data Analytics in R: A Case Study Using Tidyverse
Authors: Islam Md Shariful , Farah Nusrat , Wang Tawei 
Published: August 2023

ABSTRACT
Data analytics (DA) has gained widespread attention in accounting and auditing recently. Despite the significant potential presented by DA programming languages such as R and Python, their application remains limited. This study presents the tidyverse approach of R for DA in the field of accounting. This approach can greatly benefit undergraduate or graduate accounting students without any coding knowledge. In addition, a teaching case suitable for auditing, accounting information systems, or accounting/auditing analytics classes is presented for instructors to adopt in their courses. Evidence from classrooms suggests that this approach is effective in teaching R for DA and in introducing advanced DA tools for the next generation of accountants.
JEL Classifications: C8; Y1.
A Case Study Using Data Analytics to Detect Hail Damage Insurance Claim Fraud
Authors: Cheng Christine , Lee Chih-Chen 
Published: August 2023

ABSTRACT
Employers require that accounting students think critically and use data analytics tools to gain valuable insights for forensic, tax, auditing, and advisory services. This case provides students with a hands-on learning experience using data analytics and encourages critical thinking. Students are tasked with using Alteryx and Tableau to prepare and analyze a fictitious storm dataset and insurance claims dataset to identify claims that may be suspicious. They create visualizations and spreadsheets that support their recommendation for further analysis. The learning objectives are: (1) develop student knowledge and ability to conduct data preparation through the “Extract, Transform, and Load” (ETL) process; (2) expand student knowledge of data analytics and fraud investigation; (3) provide students with practice in fraud investigation skills, including critical thinking and problem solving; (4) develop skills specific to data analytics and data visualization in accounting; and (5) develop effective oral and written communication skills.
Forecast Rounding, Forecast Uncertainty, Managers’ Language, and Investors’ Judgments
Authors: Buchanan Jessica L. , Piercey M. David 
Published: August 2023

ABSTRACT
We investigate how rounded (e.g., 10 percent) versus unrounded (e.g., 9.73 percent, 10.00 percent, or 10.27 percent) sales growth forecasts impact investor judgment. We hypothesize that investors are more willing to invest in a company when the degree of rounding matches the amount of forecast uncertainty (i.e., rounded forecasts in more uncertain environments and unrounded forecasts in less uncertain environments). We also hypothesize that managers can offset the negative impact of a mismatch between forecast rounding and forecast uncertainty by using more immediate language in their forecasts. In a first experiment using M.B.A. students as investors, we find a combination of support and partial support for our hypotheses. However, in a second experiment using online workers and a third experiment using M.B.A. students, we fail to find support for our hypotheses. Overall, we fail to find replicable effects of forecast rounding, forecast uncertainty, and language immediacy on investors’ judgments.
The Impact of Internal Governance on Conservatism: Evidence from Australia
Authors: Liew Millie , Cao June 
Published: August 2023

ABSTRACT
Financial reporting decisions can be influenced by the distribution of executive decision-making power. We examine whether internal governance, the process through which the power to make decisions is distributed between CEOs and their subordinates, can influence the level of conservatism in such decisions. We show that firms with better internal governance are more conservative. We also find that the effect is more pronounced for firms with less powerful and older CEOs, those with subordinate executives who contribute more, and those who are more mature. We conduct various tests that confirm the robustness of our results. Unlike other studies that focus only on CEOs, we examine how the top management team as a group and the power distribution between CEOs and key subordinates shape financial reporting quality. Our study can inform various stakeholders, including firms aiming to appoint executives and strengthen their internal governance.
JEL Classifications: G34; M12; M41; M50.
Tax Avoidance and Firm Risk: New Insights from a Latent Class Mixture Model
Authors: Hutchens Michelle , Rego Sonja O. , Williams Brian 
Published: August 2023

ABSTRACT
We examine the relations between tax avoidance and two components of firm risk (priced risk and idiosyncratic risk) using latent class mixture models. OLS regressions suggest that tax avoidance is negatively related to both priced risk and idiosyncratic risk. However, results from latent class mixture models reveal that 35.6 (58) percent of the sample exhibits a significant positive association between tax avoidance and priced (idiosyncratic) risk and firm characteristics are strikingly different across the latent classes. We use these differences to develop parsimonious models to predict latent class assignments, which we then use to demonstrate that firms predicted to have a positive relation between tax avoidance and priced risk or idiosyncratic risk have more negative future tax outcomes, including higher relative cash tax rate volatility, larger additions to tax reserves, larger payouts to tax authorities, and more negative tax-related news coverage over the following three years.
Data Availability: Data are available from the public sources cited in the text.
JEL Classifications: M41; G12; D81.
Municipal Bond Credit Rating Access and Retail Investors’ Transaction Costs
Authors: Zhang Vincent 
Published: August 2023

ABSTRACT
In 2010, the Municipal Securities Rulemaking Board proposed a rule change requiring the display of current credit ratings on the EMMA website, a centralized repository of municipal bond information. Before the rule change, current credit ratings were freely available on individual rating agencies’ websites or on EMMA if municipalities provided relevant continuing disclosures, making it unclear whether the rule change would benefit investors. A difference-in-differences analysis reveals the rule change is associated with a 6–8 basis-point decrease in investor transaction costs. This effect is concentrated among the intended beneficiaries (retail investors) when credit risk information demand is high (long-maturity bonds) and current credit rating information on EMMA is low (no continuing disclosure of rating changes was provided on EMMA). The rule change appears to have helped retail investors become aware of current credit ratings by filling a disclosure gap on EMMA for municipalities without continuing disclosures of rating changes.
Modul Elektronik Berbasis Project Based Learning Pembelajaran IPAS untuk Meningkatkan Hasil Belajar Siswa Sekolah Dasar
Authors: Antari Putu Lusi , Widiana I Wayan , Wibawa I Made Citra 
Published: August 2023

Rendahnya motivasi belajar yang berdampak langsung pada hasil belajar IPAS siswa. Pendidikan dituntut untuk mengikuti perkembangan zaman dan kemajuan teknologi informasi sehingga penyediaan modul ajar yang sesuai karakteristik siswa sangat perlu dikembangkan. Salah satu media yang sesuai dengan perkembangan TIK yaitu modul elektronik sebagai bahan ajar. Penelitian ini bertujuan untuk menciptakan E-modul Berbasis Project Based Learning pada pembelajaran IPAS yang valid, praktis dan efektif untuk meningkatkan hasil belajar siswa kelas IV SD. Penelitian ini merupakan penelitian pengembangan dengan model ADDIE. Subjek penelitian ini terdiri atas 2 ahli materi, media, bahasa, siswa kelas IV sebanyak 32 orang, dan 6 orang guru. Data dikumpulkan melalui metode kuesioner dan tes. Instrumen penelitian ini meliputi lembar kuesioner validitas dan kepraktisan, serta tes hasil belajar IPAS. Hasil penelitian menunjukkan bahwa E-modul yang dikembangkan memiliki tingkat validitas Sangat Valid dari ahli media, ahli bahasa, dan ahli materi. E-modul berbasis PjBL ini juga mempunyai tingkat kepraktisan sangat praktis serta efektif untuk meningkatkan hasil belajar IPAS kelas IV SD. Penelitian ini memberikan implikasi terhadap pembelajaran khususnya bagi siswa dimana mereka dapat mengakses materi tanpa batasnya ruang dan waktu, serta dapat membantu meningkatkan hasil belajar IPAS siswa.
PERAN INTERNATIONAL ORGANIZATION FOR MIGRATION DALAM MENANGANI PERDAGANGAN MANUSIA DI INDONESIA THE ROLE OF INTERNATIONAL ORGANIZATION FOR MIGRATION IN DEALING WITH HUMAN TRAFFICKING IN INDONESIA
Authors: Ramadhani Salsabila Rizky , Haryadi Fizahri Azainafis , Apsari Nurliana Cipta 
Published: August 2023

ABSTRAKKasus human trafficking yang terjadi di Indonesia bukanlah hal baru lagi, kejadian tersebut terjadi di beberapa tempat dan telah memakan banyak korban jiwa yang juga merupakan para TKI yang bekerja di luar negeri. Indonesia bukan hanya sebagai negara sumber dalam perdagangan manusia melainkan juga sebagai negara transit dan tujuan dari human trafficking. Tentunya hal ini sangat meresahkan dan mengkhawatirkan dimana pengertian dari human trafficking atau perdagangan manusia itu sendiri sangat menakutkan, yaitu perdagangan manusia yang memiliki tujuan untuk kerja paksa dan perbudakan seksual atau eksploitasi seksual komersial bagi pedagang atau orang lain. Oleh karena itu, dalam menangani kasus human trafficking di Indonesia diperlukan peran dari organisasi non pemerintah atau biasa disebut dengan Lembaga Swadaya Masyarakat (LSM) yaitu International Organization for Migration (IOM) dalam membantu mengatasi perdagangan manusia di Indonesia. Penelitian ini bertujuan untuk menganalisis bagaimana peran yang bisa diambil oleh organisasi non-pemerintah, salah satunya adalah IOM dan peran pekerja sosial dalam menangani isu human trafficking ini. IOM telah aktif memberikan kontribusi pada upaya Indonesia untuk memerangi perdagangan manusia dengan melakukan pendampingan dan perlindungan terhadap korban dan memberikan bantuan pemulangan, dan pemulihan. ABSTRACTThe case of human trafficking that occurred in Indonesia is not new anymore, the incident occurred in several places and has claimed many lives who are also Indonesian migrant workers working abroad. Indonesia is not only a source country in human trafficking but also as a transit country and a destination for human trafficking. Of course, this is very disturbing and worrying where the notion of human trafficking or human trafficking itself is very scary, namely human trafficking which has the purpose of forced labor and sexual slavery or commercial sexual exploitation for traffickers or other people. Therefore, in dealing with human trafficking cases in Indonesia, the role of non-governmental organizations or commonly referred to as Non-Governmental Organizations (NGOs), namely the International Organization for Migration (IOM) is needed in helping to overcome human trafficking in Indonesia. This study aims to analyze how the role that can be taken by non-governmental organizations, one of which is IOM and the role of social workers in dealing with the issue of human trafficking. IOM has actively contributed to Indonesia's efforts to combat trafficking in persons by providing assistance and protection to victims and providing repatriation and recovery assistance.
PERAN BADAN KERJASAMA ANTAR DESA DALAM PERLINDUNGAN, PENGELOLAAN, PELESTARIAN HASIL PELAKSANAAN PROGRAM NASIONAL PEMBERDAYAAN MASYARAKAT MANDIRI KABUPATEN BANYUASIN
Authors: Aryanisila Aryanisila 
Published: August 2023

This studies audit modified into carried out to find out the general safety, manage, and conservation efforts that had been carried out to provide criminal guarantees, preserve sustainability, and increase the outcomes of the participatory trends that have been set up via PNPM and facilitated thru the guarantees). The trouble confronted thru BKAD is that it is a sustainable arrears from the SPP group in Banyuasin. This studies takes up the issue via the use of investigating the location of BKAD in defensive, coping with, and keeping the consequences of the implementation of PNPM in Banyuasin. The qualitative qualitative technique have become selected to study the trouble this is being investigated. The research statistics had been amassed through in-intensity interviews, observations, and documentation. The self-discipline of informants was done with the aid of way of purposive sampling and snowball sampling. Records is verified via regular participation, declaration, member checking, and triangulation. The information had been analyzed qualitatively, which consisted of facts collection, facts reduction, data presentation, and statistics verification. The research findings cowl three problems. First, BKAD takes safeguards aimed at inventorying SPP assets and properties through discussions. 2nd, BKAD carries out a manage software by using manner of restructuring consumer loans, taking element with all the corporations worried in PNPM. 0.33, the conservation efforts completed with the aid of using BKAD have resulted in sustainable SPP.
Social Media: An Exploratory Study of Information, Misinformation, Disinformation, and Malinformation
Authors: Hussain Mumtaz , Soomro Tariq Rahim 
Published: August 2023

Abstract
The widespread use of social media all around the globe has affected the way of life in all aspects, not only for individuals but for businesses as well. Businesses share their upcoming events, reveal their products, and advertise to their potential customers, where individuals use social media to stay connected with their social circles, get updates and news from social media pages of news agencies, and update their information regarding the latest activities, businesses, economy, events, politics, trends, and about their area of interest. According to Statista, there were 4.59 billion users of social media worldwide in 2022 and expected to grow up to 5.85 billion in the year 2027. With its massive user base, social media does not only generate useful information for businesses and individuals, but at the same time, it also creates an abundance of misinformation and disinformation as well as malinformation to acquire social-political or business agendas. Individuals tend to share social media posts without checking the authenticity of the information they are sharing, which results in posts having misinformation, disinformation, or malinformation becoming viral around the world in a matter of minutes. Identifying misinformation, disinformation, and malinformation has become a prominent problem associated with social media.
PhoBERT: Application in Disease Classification based on Vietnamese Symptom Analysis
Authors: Nguyen Hai Thanh , Huynh Tuyet Ngoc , Mai Nhi Thien Ngoc , Le Khoa Dang Dang , Thi-Ngoc-Diem Pham 
Published: August 2023

Abstract
Besides the successful use of support software in cutting-edge medical procedures, the significance of determining a disease early signs and symptoms before its detection is a growing pressing requirement to raise the standard of medical examination and treatment. This creates favourable conditions, reduces patient inconvenience and hospital overcrowding. Before transferring patients to an appropriate doctor, healthcare staff must have the patient’s symptoms. This study leverages the PhoBERT model to assist in classifying patients with text classification tasks based on symptoms they provided in the first stages of Vietnamese hospital admission. The outcomes of PhoBERT on more than 200 000 text-based symptoms collected from Vietnamese hospitals can improve the classification performance compared to Bag of Words (BOW) with classic machine learning algorithms, and some considered deep learning architectures such as 1D-Convolutional Neural Networks and Long Short-Term Memory. The proposed method can achieve promising results to be deployed in automatic hospital admission procedures in Vietnam.
UW Deep SLAM-CNN Assisted Underwater SLAM
Authors: Amarasinghe Chinthaka , Ratnaweera Asanga , Maitripala Sanjeeva 
Published: August 2023

Abstract
Underwater simultaneous localization and mapping (SLAM) poses significant challenges for modern visual SLAM systems. The integration of deep learning networks within computer vision offers promising potential for addressing these difficulties. Our research draws inspiration from deep learning approaches applied to interest point detection and matching, single image depth prediction and underwater image enhancement. In response, we propose 3D-Net, a deep learning-assisted network designed to tackle these three tasks simultaneously. The network consists of three branches, each serving a distinct purpose: interest point detection, descriptor generation, and depth prediction. The interest point detector and descriptor generator can effectively serve as a front end for a classical SLAM system. The predicted depth information is akin to a virtual depth camera, opening up possibilities for various applications. We provide quantitative and qualitative evaluations to illustrate some of these potential uses. The network was trained in in several steps, using in-air datasets and followed by generated underwater datasets. Further, the network is integrated into feature-based SALM systems ORBSLAM2 and ORBSSLAM3, providing a comprehensive assessment of its effectiveness for underwater navigation.
Classification of COVID-19 Chest X-Ray Images Based on Speeded Up Robust Features and Clustering-Based Support Vector Machines
Authors: Rajab Maher I. 
Published: August 2023

Abstract
Due to the worldwide deficiency of medical test kits and the significant time required by radiology experts to identify the new COVID-19, it is essential to develop fast, robust, and intelligent chest X-ray (CXR) image classification system. The proposed method consists of two major components: feature extraction and classification. The Bag of image features algorithm creates visual vocabulary from two training data categories of chest X-ray images: Normal and COVID-19 patients’ datasets. The algorithm extracts salient features and descriptors from CXR images using the Speeded Up Robust Features (SURF) algorithm. Machine learning with the Clustering-Based Support Vector Machines (CB-SVMs) multiclass classifier is trained using SURF features to classify the CXR image categories. The careful collection of ground truth Normal and COVID-19 CXR datasets, provided by worldwide expert radiologists, has certainly influenced the performance of the proposed CB-SVMs classifier to preserve the generalization capabilities. The high classification accuracy of 99 % demonstrates the effectiveness of the proposed method, where the accuracy is assessed on an independent test sets.
Inquisitive Genetic-Based Wolf Optimization for Load Balancing in Cloud Computing
Authors: Sansanwal Suman , Jain Nitin 
Published: August 2023

Abstract
Cloud remains an active and dominant player in the field of information technology. Hence, to meet the rapidly growing requirement of computational processes and storage resources, the cloud provider deploys efficient data centres globally that comprise thousands of IT servers. Because of tremendous energy and resource utilization, a reliable cloud platform has to be necessarily optimized. Effective load balancing is a great option to overcome these issues. However, loading balancing difficulties, such as increased computational complexity, the chance of losing the client data during task rescheduling, and consuming huge memory of the host, and new VM (Virtual Machine), need appropriate optimization. Hence, the study aims to create a newly developed IG-WA (Inquisitive Genetic–Wolf Optimization) framework that meritoriously detects the optimized virtual machine in an environment. For this purpose, the system utilises the GWO (Grey Wolf Optimization) method with an evolutionary mechanism for achieving a proper compromise between exploitation and exploration, thereby accelerating the convergence and achieving optimized accuracy. Furthermore, the fitness function evaluated with an inquisitive genetic algorithm adds value to the overall efficacy. Performance evaluation brings forward the outperformance of the proposed IGWO system in terms of energy consumption, execution time and cost, makespan, CPU utilization, and memory utilization. Further, the system attains more comprehensive and better results when compared to the state of art methods.