Data Analysis Tools Research Articles

Review on audit data visualization method based on R language

To be competitive in today's market, companies must constantly assess and improve their operations, and financial data analysis has emerged as a crucial tool for this purpose. Executives can utilize data analysis to gain a deeper understanding of the underlying facts in their data and make better informed decisions about their company and the market. Multiple data models in the language make it possible to have a fully functional language environment with tools for statistical analysis and visual visualization of data. With its ability to enhance the quality of work in statistical computations and graphical analysis, the R language is ideally suited to the industrial data analysis environment. In this paper, we use a literature review methodology to examine the domestic and international literature on R language big data visualization auditing, analyze the visualization application areas of R language big data auditing, discuss the benefits and challenges of big data auditing, demonstrate how R language can be adapted to real-world auditing scenarios, and offer reasonable recommendations and optimistic outlooks for the field's future.

ChatGPT Role in a Medical Survey

Significant progress has been made in AI over the past decade, but its application in clinical care remains limited. However, ChatGPT, an advanced language model developed by OpenAI, shows great promise in medicine and can significantly impact medical surveys by improving data collection and generating valuable insights for better healthcare outcomes. ChatGPT has the potential to enhance survey research by assisting in various aspects, including survey design, sampling, data cleaning, analysis, and reporting, improving the quality and efficiency of the research process. AI chatbots like ChatGPT in survey administration can enhance response rates and participant engagement, providing a better user experience and capturing more comprehensive data. Numerous studies have demonstrated ChatGPT's impressive performance in clinical reasoning exams, addressing complex questions in pathology, microbiology, and life support scenarios, making it a valuable tool for data analysis and decision-making in healthcare. While using ChatGPT in medical surveys offers advantages such as accessibility, language versatility, knowledge democratization, and efficiency, there are also disadvantages, including response sensitivity, data limitations, accuracy concerns, bias, and limited access to recent literature. Ethical concerns in AI healthcare include privacy issues, mistrust in AI systems, societal prejudices, and racial biases, which can be addressed through privacy protection measures, transparency, trust-building efforts, bias mitigation strategies, and involving relevant stakeholders in the process.

Aspects of Identity and Worklife Balance of Service Crew in a Fastfood Industry

The purpose of this quantitative, non-experimental descriptive-correlational study was to determine the significant influence of aspects of identity to the work-life balance of service crew in a fast-food industry. Adapted, standardized questionnaires were used in the collecting data from 400 respondents, selected through cluster sampling approach. The data were collecting through face to face survey. Data analysis tools used were weighted mean, Pearsons-r, and regression analysis. Results showed that all the indicators of aspects of identity, to wit, personal identity orientation, relational identity orientation, social identity orientation and collective identity orientation, are all in high levels. Also, the indicators of work-life balance, to wit, support family, childcare dependent care, self management, personal life expectation, personal life satisfaction, work-life balance policies, workplace support, workload, financial assistance, work expectations and work satisfaction are in high level. It was also found out that the aspects of identity has significant relationship to work-life balance of service crew in a fast food industry. With regression analysis, social identity orientation, collective identity orientation, and personal identity orientation are the domains of aspects of identity that have significant influence to work-life balance. Of the three domains, social identity orientation was observed to be the best predictor of work-life balance

Innovative solutions for disease management

The increasing prevalence of chronic diseases is a driver for emerging big data technologies for healthcare including digital platforms for data collection, systems for active patient engagement and education, therapy specific predictive models, optimized patient pathway models. Powerful bioelectronic medicine tools for data collection, analysis and visualization allow for joint processing of large volumes of heterogeneous data, which in turn can produce new insights about patient outcomes and alternative interpretations of clinical patterns that can lead to implementation of optimized clinical decisions and clinical patient pathway by healthcare professionals.With this perspective, we identify innovative solutions for disease management and evaluate their impact on patients, payers and society, by analyzing their impact in terms of clinical outcomes (effectiveness, safety, and quality of life) and economic outcomes (cost-effectiveness, savings, and productivity).As a result, we propose a new approach based on the main pillars of innovation in the disease management area, i.e. progressive patient care models, patient-centric approaches, bioelectronics for precise medicine, and lean management that, combined with an increase in appropriate private-public-citizen-partnership, leads towards Patient-Centric Healthcare.

Tri©DB: an integrated platform of knowledgebase and reporting system for cancer precision medicine

BackgroundWith the development of cancer precision medicine, a huge amount of high-dimensional cancer information has rapidly accumulated regarding gene alterations, diseases, therapeutic interventions and various annotations. The information is highly fragmented across multiple different sources, making it highly challenging to effectively utilize and exchange the information. Therefore, it is essential to create a resource platform containing well-aggregated, carefully mined, and easily accessible data for effective knowledge sharing.MethodsIn this study, we have developed “Consensus Cancer Core” (Tri©DB), a new integrative cancer precision medicine knowledgebase and reporting system by mining and harmonizing multifaceted cancer data sources, and presenting them in a centralized platform with enhanced functionalities for accessibility, annotation and analysis.ResultsThe knowledgebase provides the currently most comprehensive information on cancer precision medicine covering more than 40 annotation entities, many of which are novel and have never been explored previously. Tri©DB offers several unique features: (i) harmonizing the cancer-related information from more than 30 data sources into one integrative platform for easy access; (ii) utilizing a variety of data analysis and graphical tools for enhanced user interaction with the high-dimensional data; (iii) containing a newly developed reporting system for automated annotation and therapy matching for external patient genomic data. Benchmark test indicated that Tri©DB is able to annotate 46% more treatments than two officially recognized resources, oncoKB and MCG. Tri©DB was further shown to have achieved 94.9% concordance with administered treatments in a real clinical trial.ConclusionsThe novel features and rich functionalities of the new platform will facilitate full access to cancer precision medicine data in one single platform and accommodate the needs of a broad range of researchers not only in translational medicine, but also in basic biomedical research. We believe that it will help to promote knowledge sharing in cancer precision medicine. Tri©DB is freely available at www.biomeddb.org, and is hosted on a cutting-edge technology architecture supporting all major browsers and mobile handsets.

Metabolomics of natural samples: A tutorial review on the latest technologies.

Metabolomics is the study of metabolites present in a living system. It is a rapidly growing field aimed at discovering novel compounds, studying biological processes, diagnosing diseases, and ensuring the quality of food products. Recently, the analysis of natural samples has become important to explore novel bioactive compounds and to study how environment and genetics affect living systems. Various metabolomics techniques, databases, and data analysis tools are available for natural sample metabolomics. However, choosing the right method can be a daunting exercise because natural samples are heterogeneous and require untargeted approaches. This tutorial review aims to compile the latest technologies to guide an early-career scientist on natural sample metabolomics. First, different extraction methods and their pros and cons are reviewed. Second, currently available metabolomics databases and data analysis tools are summarized. Next, recent research on metabolomics of milk, honey, and microbial samples is reviewed. Finally, after reviewing the latest trends in technologies, a checklist is presented to guide an early-career researcher on how to design a metabolomics project. In conclusion, this review is a comprehensive resource for a researcher planning to conduct their first metabolomics analysis. It is also useful for experienced researchers to update themselves on the latest trends in metabolomics.

THE EFFECT OF WORK ENVIRONMENT AND ORGANISATIONAL CULTURE ON WORK PRODUCTIVITY

The purpose of this study was to analyse how the influence of work environment and organisational culture on employee productivity at PT Maju Bersama Gemilang, with a quantitative approach. The population in this study were all employees of the production department. The sampling technique used probability sampling as many as 76 employees as respondents in this study. The data processing method uses SPSS software. The data analysis tool used in this study is multiple linear regression. The results of this research indicate that the work environment has a significant effect on employee productivity. The results of the regression equation show that the work environment has a positive influence on employee productivity. The results of the calculation of organisational culture have a significant effect on employee work productivity. The results of the regression equation show that organisational culture has a positive influence on employee work productivity.

Analysis of e-Service Quality, e-Trust, Promotion, e-Customer Satisfaction, and e-Customer Loyalty of Flip Application Customers in the Special Region of Yogyakarta

This research aims to find how service quality, e-trust, and promotion affect customer loyalty mediated by e-customer satisfaction with the Flip application in the Special Region of Yogyakarta. This research uses purposive sampling techniques. The number of samples used in this research was 105 respondents. The data analysis tool used in this research is Partial Least Square. The results in this study are (1) e-service quality positively affects customer satisfaction; (2) e-service quality positively affects customer loyalty; (3) e-trust positively affects customer satisfaction; (4) e-trust positively affects customer loyalty; (5) promotion positively affects customer satisfaction; (6) e-customer satisfaction positively affects customer loyalty; (7) e-service quality positively affects customer loyalty through e-customer satisfaction; (8) e-trust positively affects customer loyalty through e-customer satisfaction; and (9) promotion positively affects customer loyalty through e-customer satisfaction. The research team suggests that Flip companies pay more attention to e-service quality through several indicators, such as improving the application to avoid frequent errors, compensating users if an application system error occurs during transactions, and providing better service assistance contacts.

The Influence of Organizational Culture and the Role of Internal Auditors on Fraud Prevention, with Internal Control Systems as Mediators: A Case Study on IGE

The purpose of this research is to examine the influence of organizational culture and the role of internal auditors on fraud prevention, with internal control systems as a mediator. This study utilizes primary data by distributing questionnaires to employees working at IGE (General Inspection of the State) and five Ministries, namely the Ministry of Agriculture, Ministry of Transportation and Communication, Ministry of Health, State Ministry, and the Ministry of Higher Education. The sampling is done using the census sample method, with 100 employees as the sample in this research. The analysis method used to test hypotheses is path analysis using the SmartPLS data analysis tool version 4.0. The results of this study indicate that organizational culture influences fraud prevention, the role of internal auditors influences fraud prevention, organizational culture influences internal control systems (SPI), the role of internal auditors does not influence SPI, SPI influences fraud prevention, organizational culture influences fraud prevention through SPI, and the role of internal auditors influences fraud prevention through SPI.

Usability of Medical Data Analysis Tool

Abstract This article deals with the issue of usability of an exploratory data analysis tool in the field of medicine. The text portion contains a description of the methods and the visualization procedure. It analyses the current state on usability, medical data visualization and presents the benefits of visualization tools. The goal of this research was to design and implement a suitable visualization tool for the provided dataset, which is the result of cooperation between Technical university of Košice and East Slovak Institute of Heart and Vascular Diseases (VÚSCH) and presents cardiovascular disease data. The resulting web application aimed to provide potential users with an overview of cardiovascular diseases and the influence of their lifestyle on the assumption of such a disease, and for experts to provide different forms of viewing the given data, as well as to facilitate their work. The application was then tested for usability in two iterations where corrections and improvements were made based on the given feedback. Thanks to this iterative procedure and careful reflection of the user feedback the application received endorsement as a valuable tool by the expert evaluator.

Integrated AD trial data from multiple sources and stakeholders

AbstractThere is every reason to cheer recent advances is treatments and diagnostics for Alzheimer’s and other dementias, but enormous need remains, and progress is still too slow. An important way to accelerate new discoveries is through sharing of the vast amounts of relevant data, especially the data collect from human research participants. There is consensus among many researchers, clinicians, patients, and governments that data sharing accelerates science by increasing the utility of data. This allows for new analysis, meta‐analysis, and replication, inspiring new ideas and approaches.There are, however, challenges to data sharing. These include accessible and affordable infrastructure, tools, and resources to support data curation, sharing, and analysis. There also needs to be more incentives – to move away from siloed efforts and towards global collaboration.The Alzheimer’s Disease Data Initiative (ADDI) is dedicated to data sharing by advancing solutions to these challenges. The AD Workbench provides researchers with the infrastructure to share data and to discover data within a secure, cloud‐based environment.For data contributors, supports and resources are available to assist with harmonization and curation of data. There are also options available regarding permissioned access, whether the data is simply accessed on the AD Workbench or through federated sharing. For researchers, the AD Workbench offers compute resources, data analysis tools, and other resources to help advance their work.To both support work on the AD Workbench and to foster community and collaboration, AD Connect offers resource libraries, discussion forums, and other helpful information. We know that meaningful ADRD advances will not be made by any one person or organization. Bringing researchers together, to engage, interact, and inspire each other will help us move closer to fundamentally transforming ADRD research.

A MULTIPLE CASE STUDY ON IN-PRISON TREATMENT OF PERSONS DEPRIVED OF LIBERTY IN A PENAL COLONY WITHOUT WALLS

This case study aimed to understand the lived experiences of the Persons Deprived of Liberty of Iwahig Prison and Penal Farm in Puerto Princesa City. The study utilized a qualitative research design using multiple case study approach, with seven Persons Deprived of Liberty chosen through purposive sampling. Coding type of analysis was used as a data analysis tool. Results revealed, that the PDL were experiencing just and humane treatment from the jail officers especially that they were provided meaningful and useful activities and programs. On the challenges and coping mechanisms, they mentioned that challenges are triggered by different factors and their coping mechanisms are varied and it is important for their survival inside the correctional facility. Further, their insights were shared by giving lessons they discovered through individual liberty deprivation. The lived experiences of the PDL are eye opener to the whole community, to support them in order to provide them a social service intervention meant to address the issues and difficulties encountered by the PDL, this support will bring great impact as it will transform the lives of the PDL. KEYWORDS: In-prison treatment, Persons deprived of liberty, transformation, case study, Puerto Princesa City, Philippines

Can data save small businesses? Benefits and challenges of data analytics adoption among small-sized retailers

Small businesses were recently hit hard by the COVID-19 pandemic, and there has been a crucial need for them to meet changing consumer behaviour and industry trends through data analytics. The purpose of this study is to understand the status of the adoption and utilisation of data analytics among small-sized retailers. Through in-depth interviews with US small business owners in the retail industry, the findings provide an overview of data analytics implementation status among small businesses. With regard to technological factors, the advantages of data analytics utilisation were identified (ie a better understanding of customers, strategic decision making, optimisation of marketing tools and accurate sales/trends forecast). Technological difficulties in understanding data and data analytics tools appeared as challenges. With regard to organisational factors, the small size of the firm and top management support were identified to be influential factors in the data analytics adoption process. However, lack of time, training resources and human resources were identified as major organisational challenges. As for environmental factors, macroeconomic contexts such as the COVID-19 pandemic and dynamic market trends influenced small businesses to adopt data analytics. Based on the technology-organisation-environment framework, the findings contribute to SME research and become a stepping stone to deriving a new framework.

Automated progress measurement using computer vision technology in UK construction

A critical concern with the UK’s construction project progress monitoring and control techniques is their dependency on data collection, which is time consuming and unproductive and may lead to various circumstances in managing projects. However, collecting and accurately analysing information from construction sites requires the development of technologies. As key artificial intelligence (AI) technology, computer vision (CV) is a powerful tool for big data analysis that can address the aforementioned challenges. This study explores the status of CV-based construction progress monitoring (CV-CPM) adoption and the main barriers to and incentives for its adoption within the UK construction sites. In this respect, after an extensive review of the literature covering the AI technology in construction management and the concept, function and usage of CV and its integration with construction progress monitoring, including its benefits and drivers and technical challenges, a questionnaire was administered to UK construction professionals to collect their perceptions. The study results indicated that construction practitioners were relatively aware of CV-CPM but lacked competencies and skills. CV-CPM has been perceived to be relatively better than the traditional approach. Implications such as the cost of implementation, lack of expertise and resistance to change were the major challenges in CV-CPM adoption. Meanwhile, technological development, decision making and competitiveness were classified as incentives for its adoption.

Планування експортної діяльності в умовах виходу на нові ринки

Today, the concept of raising business efficiency to a higher level is a critically important direction of development of the modern Ukrainian economy. Building a sustainable and competitive economy contributes to the creation of healthy competition between various market participants, which has a significant impact on the relationship between producers and consumers. This forces manufacturers to focus their attention on the development and modernization of their products. In the long term, it plays a key role for the country as a whole. Companies all over the world develop a business plan taking into account all possible risks and force majeure circumstances. This has long since become the so-called trend of business transformation in Ukraine to determine and use their full potential. Since there is a war going on in Ukraine now, businesses have to reckon with and struggle with the new realities that it puts before us in order to develop and work to strengthen Ukraine, for the sake of defeating the common enemy. Strong government support and assistance is also critical to successful business development in wartime. The authorities should create favorable conditions for enterprises, including a simplified bureaucratic process, support in export initiatives, as well as ensuring security and stability in the regions of our country. It is important to emphasize that in wartime Ukrainian companies must be ready for a wide variety of challenges and crisis situations. They must actively develop risk management strategies to ensure the sustainability of their business and protect the interests of consumers. In addition, it is important to focus on the development and application of new technologies and innovations that can contribute to increasing the productivity and competitiveness of enterprises and business planning as a whole. This includes the use of Internet resources and various software, artificial intelligence, data analysis and other modern tools to optimize production and business management or create a business plan. That is why business planning is now a very important aspect in such a difficult period, but at the same time it is an opportunity when Ukrainian companies can become international and enter new markets.

Exploring the Relationship of Audit Committee Meetings, Independency, CEO Duality, and Firm Performance: A Study in Kuwait

By concentrating on audit committee meetings and its impact on business performance, with particular emphasis on market share (MRS), a variable that has up until now gone unexamined in current research, this study offers a novel inquiry into the field of CG. The background for this research was provided by the expanding field of CG investigations and their changing tendencies. By painstakingly examining the impact of CG structures on the financial performance of publicly traded firms in the Kuwait, our study aims to significantly contribute to such new trends. This study takes a ground-breaking approach in examining the link between audit committee meetings and company achievement, pioneering the inclusion of market share (MRS) as a critical performance criterion. Notably, the report examines a sample of 60 listed firms in financial market in the nation of Kuwait. This research carefully analyses the forecasts regarding the impact of CG dynamics on financial profitability using the financial statements of these organizations for the fiscal year 2020. The study used a cross-sectional approach to rigorously test each hypothesis raised by the investigation. The well-known statistical program SPSS 20 is used as the analytical tool for data analysis. The results of this thorough examination produce interesting results. Notably, a link between audit committee meetings and company financial performance is discovered, highlighting the importance of these meetings as a catalyst for improved financial outcomes. It's intriguing that the empirical analyses go a step further and reveal about no discernible link between the number of independency and financial performance. Similar to this, the research's findings show that the idea of CEO duality—in which the CEO also serves as the board's chair—has no appreciable effect on a company's financial performance.

The use of R in forestry research

Abstract The field of forestry research has greatly benefited from the integration of computational tools and statistical methods in recent years. Among these tools, the programming language R has emerged as a powerful and versatile platform for forestry research, ranging from data analysis, modeling to visualization. However, the key trends in general reported R use and patterns in forestry research remain unknown. We analyzed R and R package usage frequencies for 14 800 research articles published in eight top forestry journals across a span of 10 years, from 2013 to 2022. Among these articles, a notable number of 6790 (accounting for 45.7%) explicitly utilized R as their primary tool for data analysis. The adoption of R exhibited a linear growth trend, rising from 28.3% in 2013 to 60.9% in 2022. The top five used packages reported were vegan, lme4, nlme, MuMIn, and ggplot2. Diverse journals have their unique areas of emphasis, resulting in disparities in the frequency of R package application among journals. The average number of R packages used per article also showed an increasing trend over time. The study underscores the recognition that R, with its powerful data statistical and visualization capabilities, plays a pivotal role in enabling researchers to conduct thorough analyses and acquire comprehensive insights into various aspects of forestry science.

Permutation entropy-based characterization of speckle patterns generated by semiconductor laser light

Semiconductor lasers with optical feedback are stochastic nonlinear systems that can display complex dynamics and abrupt changes when their operation conditions change. Even very small changes can lead to large variations in the spatial and spectral properties of the laser emission. This makes a semiconductor laser with feedback an ideal system for conducting controlled experiments to test data analysis tools to detect and characterize transitions. Here, we identify feedback-induced transitions by analyzing speckle patterns that are generated after the laser light propagates in an optical fiber. Speckle patterns result from the interference of multiple modes, and their statistical properties are understood, but a direct mathematical model does not exist. Here we show the versatility of the correlation length and the permutation entropy as measures for characterizing speckle patterns. Combining entropy and correlation analysis with speckle contrast analysis, we uncover changes that occur when the laser current increases from below to well above the threshold, which unveils the effects of optical feedback on the coherence of the laser emission.

Mapping and modelling the main determinants of Migration Flows at the NUTS2 Level in European Union using Spatial Data Analysis Techniques

Abstract Spatial data analysis approaches have grown in popularity in recent years as there has been an increased interest in studying migration at the regional level. We employed in our analysis the Nomenclature of Territorial Units for Statistics (NUTS) level, which offers a more thorough view of migratory patterns inside a nation as well as among EU countries.Using spatial data analytic tools, this research aims to investigate the key determinants of international migration at the NUTS2 level. Using data from the Eurostat database, we undertake an extensive analysis of migration movements in a sample of European Union countries. We apply spatial econometric models to examine the relationship between crude rate migration and other relevant variables as independent variables. Although the available data at the NUTS2 level of regional ranking are limited, we believe that we included the most comprehensive set of relevant variables in our analysis.Our study contributes to the existing literature on migration determinants by highlighting the importance of spatial analysis techniques in understanding migration factors at the NUTS2 level.

The Role of Organizational Culture as a Mediator Between the Influence of Motivation, Leadership, and Supply Chain Management on Employee Green Behavior

This research is motivated by the important role of companies in the context of globalization, where dependence between countries is increasing. The company is a vital element in meeting the needs of the global community. The main objective of this study is to analyze how organizational culture mediates the relationship between motivation, leadership, and supply chain management to employees' green behavior. The population of this study was employees of PT. X which has a total of 592 employees, the sampling technique used is simple random sampling so that a sample of 86 employees from PT. X. The research method used is quantitative research by applying Partial Least Squares (PLS) as a data analysis tool. The results showed that motivation and leadership had a significant and positive influence on employees' green behavior. Motivation also has a significant positive influence on employees' green behavior through mediating organizational culture. In addition, organizational culture also has a significant effect on the green behavior of employees at PT. X. in Indonesia. The results of this study have important implications in the context of human resource management that cares for the environment. These results can assist companies in developing strategies to improve employees' green behavior and achieve sustainability goals.