The effect of big data on financial reporting quality

The current manuscript aimed to explain the impact of big data on the financial reporting quality of the industrial sector in Jordan. To achieve the manuscript goals and validate hypotheses, a field study was conducted by distributing a questionnaire to 325 financial managers in industrial companies listed on the Amman Stock Exchange during a specific period. Gathered data were analyzed using structural equation modeling (SEM). The manuscript concluded that the big data dimensions, including variety, volume, and velocity, had a positive impact on financial reporting quality. Therefore, a set of recommendations were provided to managers of the industrial companies in Jordan to put in place an extensive data governance system to as-sure data quality, security, privacy, and compliance. To ensure the integrity and dependability of financial reporting, define data ownership, create data quality standards, and develop processes for data access, use, and preservation

The Future Role of Machine Learning in Clinical Transplantation

The use of artificial intelligence and machine learning (ML) has revolutionised our daily lives and will soon be instrumental in healthcare delivery. The rise of ML is due to multiple factors: increasing access to massive data sets, exponential increases in processing power and key algorithmic developments which allow ML models to tackle increasingly challenging questions. Progressively more transplantation research is exploring the potential utility of ML models throughout the patient journey, although this has not yet widely transitioned into the clinical domain.In this review, we explore common approaches used in ML in solid organ clinical transplantation and consider opportunities for ML to help clinicians and patients. We discuss ways in which ML can aid leverage of large complex datasets, generate cutting-edge prediction models, perform clinical image analysis, discover novel markers in molecular data, and fuse datasets to generate novel insights in modern transplantation practice. We focus on key areas in transplantation where ML is driving progress, explore the future potential roles of ML and discuss the challenges and limitations of these powerful tools

Assessing contextual factors for sustainable development: a case study of LEED-certified projects in Jordan

PurposeThe researchers analyzed factors affecting the adoption of the Leadership in Energy and Environmental Design (LEED) green-building certification system in Jordan, including financial performance of certified projects along with broader barriers that may impact developers’ interest in LEED.Design/methodology/approachThe authors first reviewed online data for all LEED registered and certified projects in Jordan, recruited LEED-certified project stakeholders, collected documents related to LEED projects and conducted LEED category credit summaries, financial cost-benefit analyses and spot-checking reported values in local markets. The authors then visited projects sites and interviewed various project stakeholders to understand better stakeholders' decision-making processes concerning LEED and relevant factors (financial, branding, cultural, political, etc.).FindingsObtaining LEED certification in Jordan was financially feasible as evinced in both the quantitative analysis and interviews. However, the authors found that there was very limited interest in LEED among Jordanian developers. Barriers included widespread cynicism toward green building concepts as well as a lack of local expertise in installing and maintaining green technologies. To overcome these barriers, the authors recommend that green building initiatives place a greater emphasis on education and public-promotion activities.Research limitations/implicationsThe research data were limited to projects that had successfully achieved LEED certification. Broader qualitative research conducted across the Jordanian building community could provide additional insights, but such an investigation is beyond the scope of the current study.Originality/valueThe complexity of adapting a Western green building standard (LEED) to a non-Western context is discussed in detail. The findings suggest that understanding regional development challenges, local markets and cultural differences is vital for successfully implementing green building certification systems.</jats:sec

Development of an inkjet-printed electrochemical nanosensor for ascorbic acid detection

Purpose Ascorbic acid (AA) is an essential vitamin for human health. Therefore, fast and cost-effective detecting of AA is essential, whether in human or food samples. The purpose of this paper is to develop an electrochemical nanosensor for AA detection. Design/methodology/approach The proposed nanosensor was developed by printing carbon nanoparticles ink and silver nanoparticles ink on a polydimethylsiloxane (PDMS) substrate. The surface of the PDMS substrate was first treated by corona plasma. Then, the nanomaterials printer was used to deposit both inks on the substrate. The working electrode surface was modified by drop-casting of carbon nanotubes. Morphological evaluation was applied using scanning electron microscopy and cyclic voltammetry. Also, a potentiostat was used to detect AA by differential pulse voltammetry. Findings It has been shown that the developed nanosensor linearly worked at a range of (0–5 mM), with a limit of detection lower than 0.8 mM and a relative standard deviation of 6.6%. Originality/value The developed nanosensor is characterized by a simple and cost-effective sensing tool for AA. In particular, the nanomaterials enhanced the nanosensor’s sensitivity due to the high catalytic activity. </jats:sec

TELE-MONITORING SYSTEM OF RISK IN RESPIRATORY PATIENTS

In many situations, health care professionals need to evaluate the respiration rate (RR) for home patients. Moreover, when cases are more than health care providers’ capacity, it is important to follow up cases at home. In this paper, we present a complete system that enables healthcare providers to follow up with patients with respiratory-related diseases at home. The aim is to evaluate the use of a mobile phone’s accelerometer to capture respiration waveform from different patients using mobile phones. Whereas measurements are performed by patients themselves from home, and not by professional health care personnel, the signals captured by mobile phones are subjected to many unknowns. Therefore, the validity of the signals has to be evaluated first and before any processing. Proper signal processing algorithms can be used to prepare the captured waveform for RR computations. A validity check is considered at different stages using statistical measures and pathophysiological limitations. In this paper, a mobile application is developed to capture the accelerometer signals and send the data to a server at the health care facility. The server has a database of each patient’s signals considering patient privacy and security of information. All the validations and signal processing are performed on the server side. The patient’s condition can be followed up over a few days and an alarm system may be implemented at the server-side in case of respiration deterioration or when there is a risk of a patient’s need for hospitalization. The risk is determined based on respiration signal features extracted from the received respiration signal including RR, and Autoregressive (AR) moving average (ARMA) model parameters of the signal. Results showed that the presented method can be used at a larger scale enabling health care providers to monitor a large number of patients. </jats:p