| 1. |
- Muhammad, Dost, et al.
(författare)
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A Generalized Deep Learning Approach to Seismic Activity Prediction
- 2023
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Ingår i: Applied Sciences. - : MDPI. - 2076-3417. ; 13:3
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Tidskriftsartikel (refereegranskat)abstract
- Seismic activity prediction has been a challenging research domain: in this regard, accurate prediction using historical data is an intricate task. Numerous machine learning and traditional approaches have been presented lately for seismic activity prediction; however, no generalizable model exists. In this work, we consider seismic activity predication as a binary classification problem, and propose a deep neural network architecture for the classification problem, using historical data from Chile, Hindukush, and Southern California. After obtaining the data for the three regions, a data cleaning process was used, which was followed by a feature engineering step, to create multiple new features based on various seismic laws. Afterwards, the proposed model was trained on the data, for improved prediction of the seismic activity. The performance of the proposed model was evaluated and compared with extant techniques, such as random forest, support vector machine, and logistic regression. The proposed model achieved accuracy scores of 98.28%, 95.13%, and 99.29% on the Chile, Hindukush, and Southern California datasets, respectively, which were higher than the current benchmark model and classifiers. In addition, we also conducted out-sample testing, where the evaluation metrics confirmed the generality of our proposed approach.
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| 2. |
- Ahmad, Iftikhar, et al.
(författare)
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Fake News Detection Using Machine Learning Ensemble Methods
- 2020
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Ingår i: Complexity. - : WILEY-HINDAWI. - 1076-2787 .- 1099-0526. ; 2020
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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.
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| 3. |
- Ahmad, Iftikhar, et al.
(författare)
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Using algorithmic trading to analyze short term profitability of Bitcoin
- 2021
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Ingår i: PeerJ Computer Science. - : PeerJ Publishing. - 2376-5992. ; 7
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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.
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| 4. |
- Ahmad, Muhammad Ovais, Associate Professor/Lektor, et al.
(författare)
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An Empirical Investigation on Business Analytics in Software and Systems Development Projects
- 2023
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Ingår i: Information Systems Frontiers. - : Springer. - 1387-3326 .- 1572-9419. ; 25:2, s. 917-927
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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.
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| 5. |
- Ahmad, Muhammad Ovais, Associate Professor/Lektor, et al.
(författare)
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An Empirical Investigation on Electronic Government Services Continuance and Trust
- 2023
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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.
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| 6. |
- Ahmad, Muhammad Ovais, Associate Professor/Lektor, et al.
(författare)
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Early career software developers and work preferences in software engineering
- 2024
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Ingår i: Journal of Software. - : John Wiley & Sons. - 2047-7473 .- 2047-7481. ; 36:2
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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.
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| 7. |
- Yaseen, Azeema, et al.
(författare)
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Dimensionality Reduction for Internet of Things Using the Cuckoo Search Algorithm : Reduced Implications of Mesh Sensor Technologies
- 2020
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Ingår i: Wireless Communications & Mobile Computing. - : WILEY-HINDAWI. - 1530-8669 .- 1530-8677. ; 2020
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Tidskriftsartikel (refereegranskat)abstract
- The internet of things is used as a demonstrative keyword for evolution of the internet and physical realms, by means of pervasive distributed commodities with embedded identification, sensing, and actuation abilities. Imminent intellectual technologies are subsidizing internet of things for information transmission within physical and autonomous digital entities to provide amended services, leading towards a new communication era. Substantial amounts of heterogeneous hardware devices, e.g., radio frequency identification (RFID) tags, sensors, and various network protocols are exploited to support object identification and network communication. Data generated by these digital objects is termed as "Big Data" and incorporates high dimensional space with noisy, irrelevant, and redundant features. Direct execution of mining techniques onto such kind of high dimensionality attribute space can increase cost and complexity. Data analytic mechanisms are embedded into internet of things to permit intelligent decision-making capabilities. These notions have raised new challenges regarding internet of things from a data and algorithm perspective. The proposed study identifies the problem in the internet of things network and proposes a novel cuckoo search-based outdoor data management. The technique of the feature extraction is used for the extraction of expedient information from raw and high-dimensional data. After the implementation for the cuckoo search-based feature extraction, few test benchmarks are introduced to evaluate the performance of mutated cuckoo search algorithms. The consequential low-dimensional data optimizes classification accuracy along with reduced complexity and cost.
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| 8. |
- Ahmad, Muhammad Ovais, Associate Professor/Lektor
(författare)
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5G Secure Solution Development and Security Master Role
- 2024
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Ingår i: International Conference on Evaluation and Assessment in Software Engineering.
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Konferensbidrag (refereegranskat)abstract
- This paper explores the relationship between self-organisation andtailored roles in large agile software development teams. The casestudy examines a Swedish IT company that has introduced the roleof “Security Master” in Scrum teams. The teams are developing avery large and secure 5G solution. Twenty semi-structuredinterviews were conducted and deductively analysed. The resultsshed light on the Security Master role, its need, responsibilities andimpact on secure coding. The paper concludes with a discussion oflessons learned and recommendations for future research in thecontext of large, security-sensitive projects.
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| 9. |
- Ahmad, Muhammad Ovais, Associate Professor/Lektor, et al.
(författare)
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Beyond Technical Debt Unravelling Organisational Debt Concept
- 2024
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Ingår i: 39th ACM/SIGAPP Symposium On Applied Computing.
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Konferensbidrag (refereegranskat)abstract
- The development of software and systems is a complex task that involves social, technical and organisational factors. Technical debt is a well-known concept that refers to the negative consequences of taking shortcuts in software development. However, organisational debt (OD) is a less well-known phenomenon that arises due to shortcuts in the organisational structure and processes of a software organisation. The lack of a clearly defined OD makes it difficult to identify and manage this type of debt. This study presents a multi-vocabulary literature review that consolidates an understanding of the nature of OD and its impact on software organisations. OD encompasses a set of attributes, precedents and outcomes. In addition, this study highlights the five causes and mitigation strategies of OD. The results of this study indicate that software companies are facing a major issue with OD. Future research should include empirical studies to validate techniques that can assist software professionals in managing OD to address this issue.
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| 10. |
- Ahmad, Muhammad Ovais, Associate Professor/Lektor
(författare)
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Business Analytics Continuance in Software Development Projects : A Preliminary Analysis
- 2021
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Ingår i: Conference on e-Business, e-Services and e-Society. - Cham : Springer. - 9783030854461 ; , s. 622-628
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Konferensbidrag (refereegranskat)abstract
- This paper investigates factors affecting business analytics (BA) in software and systems development projects. This is the first study to examine business analytics continuance in projects from Pakistani software professional’s perspective. The data was collected from 186 Pakistani software professionals working in software and systems development projects. The data was analyzed using partial least squares structural equation modelling techniques. Our structural model is able to explain 40% variance of BA continuance intention, 62% variance of satisfaction, 69% variance of technological compatibility, and 59% variance of perceived usefulness. Technological compatibility and perceived usefulness are the significant factors that can affect BA continuance intention in software and systems projects. Surprisingly the results show that satisfaction does not affect BA continuance intention.
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