| 1. |
- Ademuyiwa, Adesoji O., et al.
(författare)
-
Determinants of morbidity and mortality following emergency abdominal surgery in children in low-income and middle-income countries
- 2016
-
Ingår i: BMJ Global Health. - : BMJ Publishing Group Ltd. - 2059-7908. ; 1:4
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Child health is a key priority on the global health agenda, yet the provision of essential and emergency surgery in children is patchy in resource-poor regions. This study was aimed to determine the mortality risk for emergency abdominal paediatric surgery in low-income countries globally.Methods: Multicentre, international, prospective, cohort study. Self-selected surgical units performing emergency abdominal surgery submitted prespecified data for consecutive children aged <16 years during a 2-week period between July and December 2014. The United Nation's Human Development Index (HDI) was used to stratify countries. The main outcome measure was 30-day postoperative mortality, analysed by multilevel logistic regression.Results: This study included 1409 patients from 253 centres in 43 countries; 282 children were under 2 years of age. Among them, 265 (18.8%) were from low-HDI, 450 (31.9%) from middle-HDI and 694 (49.3%) from high-HDI countries. The most common operations performed were appendectomy, small bowel resection, pyloromyotomy and correction of intussusception. After adjustment for patient and hospital risk factors, child mortality at 30 days was significantly higher in low-HDI (adjusted OR 7.14 (95% CI 2.52 to 20.23), p<0.001) and middle-HDI (4.42 (1.44 to 13.56), p=0.009) countries compared with high-HDI countries, translating to 40 excess deaths per 1000 procedures performed.Conclusions: Adjusted mortality in children following emergency abdominal surgery may be as high as 7 times greater in low-HDI and middle-HDI countries compared with high-HDI countries. Effective provision of emergency essential surgery should be a key priority for global child health agendas.
|
|
| 2. |
- Tran, K. B., et al.
(författare)
-
The global burden of cancer attributable to risk factors, 2010-19: a systematic analysis for the Global Burden of Disease Study 2019
- 2022
-
Ingår i: Lancet. - 0140-6736. ; 400:10352, s. 563-591
-
Tidskriftsartikel (refereegranskat)abstract
- Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.
|
|
| 3. |
- Ahmad, Iftikhar, et al.
(författare)
-
Fake News Detection Using Machine Learning Ensemble Methods
- 2020
-
Ingår i: Complexity. - : WILEY-HINDAWI. - 1076-2787 .- 1099-0526. ; 2020
-
Tidskriftsartikel (refereegranskat)abstract
- The advent of the World Wide Web and the rapid adoption of social media platforms (such as Facebook and Twitter) paved the way for information dissemination that has never been witnessed in the human history before. With the current usage of social media platforms, consumers are creating and sharing more information than ever before, some of which are misleading with no relevance to reality. Automated classification of a text article as misinformation or disinformation is a challenging task. Even an expert in a particular domain has to explore multiple aspects before giving a verdict on the truthfulness of an article. In this work, we propose to use machine learning ensemble approach for automated classification of news articles. Our study explores different textual properties that can be used to distinguish fake contents from real. By using those properties, we train a combination of different machine learning algorithms using various ensemble methods and evaluate their performance on 4 real world datasets. Experimental evaluation confirms the superior performance of our proposed ensemble learner approach in comparison to individual learners.
|
|
| 4. |
- Ahmad, Iftikhar, et al.
(författare)
-
Optimizing Pretrained Convolutional Neural Networks for Tomato Leaf Disease Detection
- 2020
-
Ingår i: Complexity. - : Hindawi Publishing Corporation. - 1076-2787 .- 1099-0526. ; 2020
-
Tidskriftsartikel (refereegranskat)abstract
- Vegetable and fruit plants facilitate around 7.5 billion people around the globe, playing a crucial role in sustaining life on the planet. The rapid increase in the use of chemicals such as fungicides and bactericides to curtail plant diseases is causing negative effects on the agro-ecosystem. The high scale prevalence of diseases in crops affects the production quantity and quality. Solving the problem of early identification/diagnosis of diseases by exploiting a quick and consistent reliable method will benefit the farmers. In this context, our research work focuses on classification and identification of tomato leaf diseases using convolutional neural network (CNN) techniques. We consider four CNN architectures, namely, VGG-16, VGG-19, ResNet, and Inception V3, and use feature extraction and parameter-tuning to identify and classify tomato leaf diseases. We test the underlying models on two datasets, a laboratory-based dataset and self-collected data from the field. We observe that all architectures perform better on the laboratory-based dataset than on field-based data, with performance on various metrics showing variance in the range 10%–15%. Inception V3 is identified as the best performing algorithm on both datasets.
|
|
| 5. |
- Ahmad, Iftikhar, et al.
(författare)
-
Using algorithmic trading to analyze short term profitability of Bitcoin
- 2021
-
Ingår i: PeerJ Computer Science. - : PeerJ Publishing. - 2376-5992. ; 7
-
Tidskriftsartikel (refereegranskat)abstract
- Cryptocurrencies such as Bitcoin (BTC) have seen a surge in value in the recent past and appeared as a useful investment opportunity for traders. However, their short term profitability using algorithmic trading strategies remains unanswered. In this work, we focus on the short term profitability of BTC against the euro and the yen for an eight-year period using seven trading algorithms over trading periods of length 15 and 30 days. We use the classical buy and hold (BH) as a benchmark strategy. Rather surprisingly, we found that on average, the yen is more profitable than BTC and the euro; however the answer also depends on the choice of algorithm. Reservation price algorithms result in 7.5% and 10% of average returns over 15 and 30 days respectively which is the highest for all the algorithms for the three assets. For BTC, all algorithms outperform the BH strategy. We also analyze the effect of transaction fee on the profitability of algorithms for BTC and observe that for trading period of length 15 no trading strategy is profitable for BTC. For trading period of length 30, only two strategies are profitable.
|
|
| 6. |
- Ahmad, Muhammad Ovais, Associate Professor/Lektor, et al.
(författare)
-
An Empirical Investigation on Business Analytics in Software and Systems Development Projects
- 2023
-
Ingår i: Information Systems Frontiers. - : Springer. - 1387-3326 .- 1572-9419. ; 25:2, s. 917-927
-
Tidskriftsartikel (refereegranskat)abstract
- To create competitive advantages, companies are leaning towards business analytics (BA) to make data-driven decisions. Nevertheless, users acceptance and effective usage of BA is a key element for its success. Around the globe, organizations are increasingly adopting BA, however, a paucity of research on examining the drivers of BA adoption and its continuance is noticeable in the literature. This is evident in developing countries where a higher number of systems and software development projects are outsourced. This is the first study to examine BA continuance in the context of software and systems development projects from the perspective of Pakistani software professionals. The data was collected from 186 Pakistani software professionals working in software and systems development projects. The data were analyzed using partial least squares - structural equation modelling techniques. Our structural model explains 45% variance on BA continuance intention, 69% variance on technological compatibility, and 59% variance on perceived usefulness. Our results show that confirmation has a direct impact on BA continuance intention in software and systems projects. The study has both theoretical and practical implications for professionals in the field of business analytics.
|
|
| 7. |
- Ahmad, Muhammad Ovais, Associate Professor/Lektor, et al.
(författare)
-
An Empirical Investigation on Electronic Government Services Continuance and Trust
- 2023
-
Konferensbidrag (refereegranskat)abstract
- Trust is an important factor that contributes to citizens' willingness to continuance use of e-gov services. However, there is a lack of prior investigation about trust and continuance use of e-gov services in Pakistan - a developing country. We propose a model to investigate citizens' trust and e-gov services' continuous use intention to fill this research gap. Our study collected data from an online survey of 558 Pakistani citizens. Using partial least squares analysis, we found that disposition to trust positively correlates with both internet and government trust. Moreover, citizen satisfaction, trust, perceived usefulness, confirmation, and perceived risk all have significant impacts on the continuous use intention of e-gov services. This research extends and validates the Expectation-Confirmation Model by exploring key factors that influence e-gov continuance use intention. As such, our study offers valuable insights for policymakers and practitioners involved in e-gov service delivery in developing countries like Pakistan. The paper also discusses our findings' implications and identifies future research directions.
|
|
| 8. |
- Ahmad, Muhammad Ovais, Associate Professor/Lektor, et al.
(författare)
-
Early career software developers and work preferences in software engineering
- 2024
-
Ingår i: Journal of Software. - : John Wiley & Sons. - 2047-7473 .- 2047-7481. ; 36:2
-
Tidskriftsartikel (refereegranskat)abstract
- Context: The software engineering researchers and practitioners echoed the needfor investigations to better understand the engineers developing software andservices. In light of current studies, there are significant associations between thepersonalities of software engineers and their work preferences. However, limitedstudies are using psychometric measurements in software engineering.Objective: We aim to evaluate attitudes of early-stage software engineers andinvestigate link between their personalities and work preferences.Method: We collected extensive psychometric data from 303 graduate-levelstudents in Computer Science programs at four Pakistani and one Swedish universityusing Five-Factor Model. The statistical analysis investigated associations betweenvarious personality traits and work preferences.Results: The data support the existence of two clusters of software engineers, one ofwhich is more highly rated across the board. Numerous correlations exist betweenpersonality qualities and the preferred types of employment for software developers.For instance, those who exhibit greater levels of emotional stability, agreeableness,extroversion, and conscientiousness like working on technical activities on a settimetable. Similar relationships between personalities and occupational choices arealso evident in the earlier studies. More neuroticism is reported in femalerespondents than in male respondents. Higher intelligence was demonstrated bythose who worked on the“entire development process”and“technical componentsof the project.”Conclusion: When assigning project tasks to software engineers, managers might usethe statistically significant relationships that emerged from the analysis of personalityattributes. It would be beneficial to construct effective teams by taking personalityfactors like extraversion and agreeableness into consideration. The study techniquesand analytical tools we use may identify subtle relationships and reflect distinctionsacross various groups and populations, making them valuable resources for bothfuture academic research and industrial practice.
|
|
| 9. |
- Ali, Salamat, et al.
(författare)
-
Experimental and Theoretical Aspects of MXenes-Based Energy Storage and Energy Conversion Devices
- 2023
-
Ingår i: Journal of Chemistry and Environment. - : Science Research Publishers (SRP). - 2959-0132. ; 2:2, s. 54-81
-
Forskningsöversikt (refereegranskat)abstract
- Transition metal carbides, nitrides, and carbonitrides (MXenes) have become an appealing framework for developing various energy applications. MXenes with van der Waals (vdW) interactions are facile, highly efficient, affordable, and self-assembled features that improve energy density. MXenes exhibit large surface area, high electric conductivity, and excellent electrochemical characteristics for various energy applications. This review summarizes and emphasizes the current developments in MXene with improved performance for energy storage or conversion devices, including supercapacitors (SCs), various types of rechargeable batteries (RBs), solar cells, and fuel cells. We discuss the crystal structures of MXenes properties of MXenes and briefly discuss them for different types of energy applications. Finally, the critical outlook and perspective for the MXene progress for applications in energy applications are also described.
|
|
| 10. |
- Ali Shah, Usman, et al.
(författare)
-
Accelerating Revised Simplex Method using GPU-based Basis Update
- 2020
-
Ingår i: IEEE Access. - : IEEE. - 2169-3536. ; 8, s. 52121-52138
-
Tidskriftsartikel (refereegranskat)abstract
- Optimization problems lie at the core of scientific and engineering endeavors. Solutions to these problems are often compute-intensive. To fulfill their compute-resource requirements, graphics processing unit (GPU) technology is considered a great opportunity. To this end, we focus on linear programming (LP) problem solving on GPUs using revised simplex method (RSM). This method has potentially GPU-friendly tasks, when applied to large dense problems. Basis update (BU) is one such task, which is performed in every iteration to update a matrix called basis-inverse matrix. The contribution of this paper is two-fold. Firstly, we experimentally analyzed the performance of existing GPU-based BU techniques. We discovered that the performance of a relatively old technique, in which each GPU thread computed one element of the basis-inverse matrix, could be significantly improved by introducing a vectorcopy operation to its implementation with a sophisticated programming framework. Second, we extended the adapted element-wise technique to develop a new BU technique by using three inexpensive vector operations. This allowed us to reduce the number of floating-point operations and conditional processing performed by GPU threads. A comparison of BU techniques implemented in double precision showed that our proposed technique achieved 17.4% and 13.3% average speed-up over its closest competitor for randomly generated and well-known sets of problems, respectively. Furthermore, the new technique successfully updated basisinverse matrix in relatively large problems, which the competitor was unable to update. These results strongly indicate that our proposed BU technique is not only efficient for dense RSM implementations but is also scalable.
|
|
