Extending IT infrastructures in the service sector organisations through enterprise resource planning – a telecom case study

Copyright @ 2012 ISEing.Service Sector Organisations (SSOs) have significantly focused on adopting and implementing Enterprise Resource Planning (ERP) systems to automate their prime business processes, enhance organisational productivity with lower costs and prompt service delivery to fulfil consumer demands. Thus, ERP systems are considered as a principal source to provide imperative information vital for strategic decision making process. On the contrary, ERP systems adoption and implementation is also highly considered as a challenging and expensive process that not only requires rigorous efforts but also demands to have an exhaustive investigation of influential factors that are critical to the adoption and implementation of ERP systems. As a result, the authors exhibit that it is of great significance to investigate this area within SSOs. In so doing, this paper thus focuses on the ERP critical success factors from five different categories such as: stakeholders; process; technology; organisation; and project based on the literature analysis. These perspectives comprise of 24 factors that are imperative for a successful ERP adoption and implementation. These factors are validated through an in-depth qualitative single case study based research. The findings from the literature and empirical demonstrate that most of the factors influencing the decision making process for ERP adoption and implementation are highly significant with exception to few that have either low or medium importance

Critical success factors in ERP implementation: A review

ERP systems have become vital strategic tools in today’s competitive business environment. This ongoing research study presents a review of recent research work in ERP systems. It attempts to identify the main benefits of ERP systems, the drawbacks and the critical success factors for implementation discussed in the relevant literature. The findings revealed that despite some organizations have faced challenges undertaking ERP implementations, many others have enjoyed the benefits that the systems have brought to the organizations. ERP system facilitates the smooth flow of common functional information and practices across the entire organization. In addition, it improves the performance of the supply chain and reduces the cycle times. However, without top management support, having appropriate business plan and vision, re-engineering business process, effective project management, user involvement and education and training, organizations can not embrace the full benefits of such complex system and the risk of failure might be at high level

Investigating factors influencing the decision making process for ERP adoption and implementation: An exploratory case study

The rapid developments in Information and Communication Technologies (ICT) have resulted into a borderless business environment along with an amplified market competition. Traversing through such a trend globally, organisations have significantly focused on adopting and implementing Enterprise Resource Planning (ERP) systems to automate their prime business processes, enhance organisational productivity with lower costs and prompt service delivery to fulfil consumer demands. Thus, ERP systems are considered as a principal source to provide imperative information vital for strategic decision making process. On the contrary, ERP systems adoption and implementation is also highly considered as a challenging and expensive process that not only requires rigorous efforts but also demands to have an exhaustive investigation of influential factors that are critical to the adoption and implementation of ERP systems. A plethora of research studies have been theorised exploring factors influencing the decision making process for ERP adoption and implementation; however, the authors claim that these studies are not filtered comprehensively in terms of the different perspectives. Notwithstanding, the implications of such research have yet to be assessed, leaving scope for timeliness and novel research. This paper thus focuses on the ERP critical success factors from five different perspectives such as: stakeholders; process; technology; organisation; and project based on the literature analysis. These perspectives comprise of 24 factors that are imperative for a successful ERP adoption and implementation, which are validated through a qualitative single case study based research. The empirical findings illustrate that these factor help realise significant benefits such as reducing costs and saving time or extra effort

Challenges and influential factors in ERP adoption and implementation

The adoption and implementation of Enterprise Resource Planning (ERP) systems is a challenging and expensive task that not only requires rigorous efforts but also demands to have a detailed analysis of such factors that are critical to the adoption or implementation of ERP systems. Many efforts have been made to identify such influential factors for ERP; however, they are not filtered comprehensively in terms of the different perspectives. This paper focuses on the ERP critical success factors from five different perspectives such as: stakeholders; process; technology; organisation; and project. Results from the literature review are presented and 19 such factors are identified that are imperative for a successful ERP implementation, which are listed in order of their importance. Considering these factors can realize several benefits such as reducing costs and saving time or extra effort

AutoScor: An Automated System for Essay Questions Scoring

The automated scoring or evaluation for written student responses have been, and are still a highly interesting topic for both education and natural language processing, NLP, researchers alike. With the obvious motivation of the difficulties teachers face when marking or correcting open essay questions; the development of automatic scoring methods have recently received much attention. In this paper, we developed and compared number of NLP techniques that accomplish this task. The baseline for this study is based on a vector space model, VSM. Where after normalisation, the baseline-system represents each essay by a vector, and subsequently calculates its score using the cosine similarity between it and the vector of the model answer. This baseline is then compared with the improved model, which takes the document structure into account. To evaluate our system, we used real essays that submitted for computer science course. Each essay was independently scored by two teachers, which we used as our gold standard. The systems’ scoring was then compared to both teachers. A high emphasis was added to the evaluation when the two human assessors are in agreement. The systems’ results show a high and promising performance

Evaluating Influenza Vaccination Practices among COPD Patients

Chronic Obstructive Pulmonary Disease (COPD) stands as a global health concern linked to considerable morbidity and mortality. In Jordan, the prevalence of COPD is substantial, but research in this area is limited. Exacerbations of COPD can lead to severe outcomes, including hospitalization and increased cardiovascular risk. Influenza is a significant trigger of exacerbations in COPD patients, and vaccination is recommended. However, studies have shown negative attitudes towards the influenza vaccine. This cross-sectional study aimed to investigate the knowledge, attitudes, practices, and intentions of COPD patients in Jordan regarding influenza vaccination. Data were collected through a custom-designed questionnaire from 300 COPD patients. The study revealed low influenza vaccination rates, with forgetfulness and lack of knowledge about vaccine effectiveness being the main barriers. Higher knowledge and positive attitudes were associated with greater intention to vaccinate. To tackle these challenges, it is recommended to implement customized health education campaigns, foster collaborations with healthcare providers, and engage in community-focused initiatives to enhance acceptance of the influenza vaccine among COPD patients in Jordan. These findings underscore the importance of addressing knowledge gaps and negative attitudes to enhance vaccine uptake and improve health outcomes for COPD patients

Predicting risk factors for thromboembolic complications in patients with sickle cell anaemia - lessons learned for prophylaxis

Objective: To assess the clinical and laboratory predictors of venous thromboembolism (VTE) in patients with sickle cell anaemia (SCA) and its relationship to morbidity and mortality. Methods: This retrospective case-control study analysed data from patients with SCA that experienced VTE compared with matched control patients with SCA but no VTE (2:1 ratio). Results: A total of 102 patients with SCA were enrolled (68 cases with VTE and 34 controls). Amongst the 68 cases (median age, 29.5 years), 26 (38.2%) presented with isolated pulmonary embolism (PE). A higher prevalence of splenectomy (73.5% versus 35.3%) was observed in the cases compared with the controls. A significantly higher prevalence of central venous catheter (CVC) insertion (42.6% versus 8.8%) was observed in the cases compared with the controls. High white blood cell counts, serum lactic dehydrogenase (LDH), bilirubin and C-reactive protein (CRP) and low haemoglobin (Hb) and HbF were significant risk factors for VTE. Forty-two cases (61.8%) developed acute chest syndrome, 10 (14.7%) had a stroke and seven (10.3%) died. Conclusions: VTE in patients with SCA has a high impact on morbidity and mortality. PE was the leading presentation of VTE, with CVC insertion, high LDH, bilirubin, CRP and white blood cell counts along with low Hb and HbF constituting other significant risk factors

Reported Adverse Effects and Attitudes among Arab Populations Following COVID-19 Vaccination: A Large-Scale Multinational Study Implementing Machine Learning Tools in Predicting Post-Vaccination Adverse Effects Based on Predisposing Factors

Background: The unprecedented global spread of coronavirus disease 2019 (COVID-19) has imposed huge challenges on the healthcare facilities, and impacted every aspect of life. This has led to the development of several vaccines against COVID-19 within one year. This study aimed to assess the attitudes and the side effects among Arab communities after receiving a COVID-19 vaccine and use of machine learning (ML) tools to predict post-vaccination side effects based on predisposing factors. Methods: An online-based multinational survey was carried out via social media platforms from June 14 to 31 August 2021, targeting individuals who received at least one dose of a COVID-19 vaccine from 22 Arab countries. Descriptive statistics, correlation, and chi-square tests were used to analyze the data. Moreover, extensive ML tools were utilized to predict 30 post vaccination adverse effects and their severity based on 15 predisposing factors. The importance of distinct predisposing factors in predicting particular side effects was determined using global feature importance employing gradient boost as AutoML. Results: A total of 10,064 participants from 19 Arab countries were included in this study. Around 56% were female and 59% were aged from 20 to 39 years old. A high rate of vaccine hesitancy (51%) was reported among participants. Almost 88% of the participants were vaccinated with one of three COVID-19 vaccines, including Pfizer BioNTech (52.8%), AstraZeneca (20.7%), and Sinopharm (14.2%). About 72% of participants experienced post-vaccination side effects. This study reports statistically significant associations (p < 0.01) between various predisposing factors and post-vaccinations side effects. In terms of predicting post-vaccination side effects, gradient boost, random forest, and XGBoost outperformed other ML methods. The most important predisposing factors for predicting certain side effects (i.e., tiredness, fever, headache, injection site pain and swelling, myalgia, and sleepiness and laziness) were revealed to be the number of doses, gender, type of vaccine, age, and hesitancy to receive a COVID-19 vaccine. Conclusions: The reported side effects following COVID-19 vaccination among Arab populations are usually non-life-threatening; flu-like symptoms and injection site pain. Certain predisposing factors have greater weight and importance as input data in predicting post-vaccination side effects. Based on the most significant input data, ML can also be used to predict these side effects; people with certain predicted side effects may require additional medical attention, or possibly hospitalization

Deep Learning for Cardiologist-level Myocardial Infarction Detection in Electrocardiograms

Myocardial infarction is the leading cause of death worldwide. In this paper, we design domain-inspired neural network models to detect myocardial infarction. First, we study the contribution of various leads. This systematic analysis, first of its kind in the literature, indicates that out of 15 ECG leads, data from the v6, vz, and ii leads are critical to correctly identify myocardial infarction. Second, we use this finding and adapt the ConvNetQuake neural network model--originally designed to identify earthquakes--to attain state-of-the-art classification results for myocardial infarction, achieving $99.43\%$ classification accuracy on a record-wise split, and $97.83\%$ classification accuracy on a patient-wise split. These two results represent cardiologist-level performance level for myocardial infarction detection after feeding only 10 seconds of raw ECG data into our model. Third, we show that our multi-ECG-channel neural network achieves cardiologist-level performance without the need of any kind of manual feature extraction or data pre-processing.Comment: Accepted to the European Medical and Biological Engineering Conference (EMBEC) 202

The challenges of a randomised placebo-controlled trial of CTO PCI vs. placebo with optimal medical therapy: The ORBITA-CTO pilot study design and protocol.

BACKGROUND: Percutaneous coronary intervention (PCI) for coronary chronic total occlusion (CTO) has been performed for the improvement of symptoms and quality of life in patients with stable angina. The ORBITA study demonstrated the role of the placebo effect in contemporary PCI in non-CTO chronic coronary syndromes. However, the benefit of CTO PCI beyond that of a placebo has not been demonstrated. AIMS: The ORBITA-CTO pilot study will be a double-blind, placebo-controlled study of CTO PCI randomising patients who have: (1) been accepted by a CTO operator for PCI; (2) experienced symptoms due to a CTO; (3) evidence of ischaemia; (4) evidence of viability within the CTO territory; and (5) a J-CTO score ≤3. METHODS: Patients will undergo medication optimisation that will ensure they are on at least a minimum amount of anti-anginals and complete questionnaires. Patients will record their symptoms on an app daily throughout the study. Patients will undergo randomisation procedures, including an overnight stay, and be discharged the following day. All anti-anginals will be stopped after randomisation and re-initiated on a patient-led basis during the 6-month follow-up period. At follow-up, patients will undergo repeat questionnaires and unblinding, with a further 2-week unblinded follow-up. RESULTS: The co-primary outcomes are feasibility (blinding) in this cohort and angina symptom score using an ordinal clinical outcome scale for angina. Secondary outcomes include changes in quality-of-life measures, Seattle Angina Questionnaire (SAQ), peak VO2, and anaerobic threshold on the cardiopulmonary exercise test. CONCLUSION: The feasibility of a placebo-controlled CTO PCI study will lead to future studies assessing efficacy. The impact of CTO PCI on angina measured using a novel daily symptom app may provide improved fidelity in assessing symptoms in patients with CTO's