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Book ; Online: Towards Knowledge-Centric Process Mining

Khan, Asjad / Huda, Arsal / Ghose, Aditya / Dam, Hoa Khanh

2023

Abstract: Process analytic approaches play a critical role in supporting the practice of business process management and continuous process improvement by leveraging process-related data to identify performance bottlenecks, extracting insights about reducing costs ...

Abstract	Process analytic approaches play a critical role in supporting the practice of business process management and continuous process improvement by leveraging process-related data to identify performance bottlenecks, extracting insights about reducing costs and optimizing the utilization of available resources. Process analytic techniques often have to contend with real-world settings where available logs are noisy or incomplete. In this paper we present an approach that permits process analytics techniques to deliver value in the face of noisy/incomplete event logs. Our approach leverages knowledge graphs to mitigate the effects of noise in event logs while supporting process analysts in understanding variability associated with event logs.
Keywords	Computer Science - Artificial Intelligence
Publishing date	2023-01-25
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Beyond fear and anger: A global analysis of emotional response to Covid-19 news on Twitter using deep learning.

Oliveira, Francisco Bráulio / Mougouei, Davoud / Haque, Amanul / Sichman, Jaime Simão / Dam, Hoa Khanh / Evans, Simon / Ghose, Aditya / Singh, Munindar P

Online social networks and media

2023 , Page(s) 100253

Abstract: The media has been used to disseminate public information amid the Covid-19 pandemic. However, the Covid-19 news has triggered emotional responses in people that have impacted their mental well-being and led to news avoidance. To understand the emotional ...

Abstract	The media has been used to disseminate public information amid the Covid-19 pandemic. However, the Covid-19 news has triggered emotional responses in people that have impacted their mental well-being and led to news avoidance. To understand the emotional response to the Covid-19 news, we study user comments on the news published on Twitter by 37 media outlets in 11 countries from January 2020 to December 2022. We employ a deep-learning-based model to identify one of the 6 Ekman's basic emotions, or the absence of emotional expression, in comments to the Covid-19 news, and an implementation of Latent Dirichlet Allocation (LDA) to identify 12 different topics in the news messages. Our analysis finds that while nearly half of the user comments show no significant emotions, negative emotions are more common. Anger is the most common emotion, particularly in the media and comments about political responses and governmental actions in the United States. Joy, on the other hand, is mainly linked to media outlets from the Philippines and news on vaccination. Over time, anger is consistently the most prevalent emotion, with fear being most prevalent at the start of the pandemic but decreasing and occasionally spiking with news of Covid-19 variants, cases, and deaths. Emotions also vary across media outlets, with Fox News having the highest level of disgust, the second-highest level of anger, and the lowest level of fear. Sadness is highest at Citizen TV, SABC, and Nation Africa, all three African media outlets. Also, fear is most evident in the comments to the news from The Times of India.
Language	English
Publishing date	2023-06-14
Publishing country	United States
Document type	News
ISSN	2468-6964
ISSN (online)	2468-6964
DOI	10.1016/j.osnem.2023.100253
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: On Privacy Weaknesses and Vulnerabilities in Software Systems

Sangaroonsilp, Pattaraporn / Dam, Hoa Khanh / Ghose, Aditya

2021

Abstract: In this digital era, our privacy is under constant threat as our personal data and traceable online/offline activities are frequently collected, processed and transferred by many software applications. Privacy attacks are often formed by exploiting ... ...

Abstract	In this digital era, our privacy is under constant threat as our personal data and traceable online/offline activities are frequently collected, processed and transferred by many software applications. Privacy attacks are often formed by exploiting vulnerabilities found in those software applications. The Common Weakness Enumeration (CWE) and Common Vulnerabilities and Exposures (CVE) systems are currently the main sources that software engineers rely on for understanding and preventing publicly disclosed software vulnerabilities. However, our study on all 922 weaknesses in the CWE and 156,537 vulnerabilities registered in the CVE to date has found a very small coverage of privacy-related vulnerabilities in both systems, only 4.45\% in CWE and 0.1\% in CVE. These also cover only a small number of areas of privacy threats that have been raised in existing privacy software engineering research, privacy regulations and frameworks, and relevant reputable organisations. The actionable insights generated from our study led to the introduction of 11 new common privacy weaknesses to supplement the CWE system, making it become a source for both security and privacy vulnerabilities.
Keywords	Computer Science - Software Engineering
Subject code	303 ; 005
Publishing date	2021-12-28
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: A Taxonomy for Mining and Classifying Privacy Requirements in Issue Reports

Sangaroonsilp, Pattaraporn / Dam, Hoa Khanh / Choetkiertikul, Morakot / Ragkhitwetsagul, Chaiyong / Ghose, Aditya

2021

Abstract: Context: Digital and physical trails of user activities are collected over the use of software applications and systems. As software becomes ubiquitous, protecting user privacy has become challenging. With the increase of user privacy awareness and ... ...

Abstract	Context: Digital and physical trails of user activities are collected over the use of software applications and systems. As software becomes ubiquitous, protecting user privacy has become challenging. With the increase of user privacy awareness and advent of privacy regulations and policies, there is an emerging need to implement software systems that enhance the protection of personal data processing. However, existing data protection and privacy regulations provide key principles in high-level, making it difficult for software engineers to design and implement privacy-aware systems. Objective: In this paper, we develop a taxonomy that provides a comprehensive set of privacy requirements based on four well-established personal data protection regulations and privacy frameworks, the General Data Protection Regulation (GDPR), ISO/IEC 29100, Thailand Personal Data Protection Act (Thailand PDPA) and Asia-Pacific Economic Cooperation (APEC) privacy framework. Methods: These requirements are extracted, refined and classified (using the goal-based requirements analysis method) into a level that can be used to map with issue reports. We have also performed a study on how two large open-source software projects (Google Chrome and Moodle) address the privacy requirements in our taxonomy through mining their issue reports. Results: The paper discusses how the collected issues were classified, and presents the findings and insights generated from our study. Conclusion: Mining and classifying privacy requirements in issue reports can help organisations be aware of their state of compliance by identifying privacy requirements that have not been addressed in their software projects. The taxonomy can also trace back to regulations, standards and frameworks that the software projects have not complied with based on the identified privacy requirements. Comment: Accepted at Journal of Information and Software Technology
Keywords	Computer Science - Software Engineering
Subject code	303 ; 005
Publishing date	2021-01-04
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Mining and Classifying Privacy and Data Protection Requirements in Issue Reports

Sangaroonsilp, Pattaraporn / Dam, Hoa Khanh / Choetkiertikul, Morakot / Ragkhitwetsagul, Chaiyong / Ghose, Aditya

2021

Abstract: Digital and physical footprints are a trail of user activities collected over the use of software applications and systems. As software becomes ubiquitous, protecting user privacy has become challenging. With the increase of user privacy awareness and ... ...

Abstract	Digital and physical footprints are a trail of user activities collected over the use of software applications and systems. As software becomes ubiquitous, protecting user privacy has become challenging. With the increase of user privacy awareness and advent of privacy regulations and policies, there is an emerging need to implement software systems that enhance the protection of personal data processing. However, existing data protection and privacy regulations provide key principles in high-level, making it difficult for software engineers to design and implement privacy-aware systems. In this paper, we develop a taxonomy that provides a comprehensive set of privacy requirements based on four well-established personal data protection regulations and privacy frameworks, the General Data Protection Regulation (GDPR), ISO/IEC 29100, Thailand Personal Data Protection Act (Thailand PDPA) and Asia-Pacific Economic Cooperation (APEC) privacy framework. These requirements are extracted, refined and classified into a level that can be used to map with issue reports. We have also performed a study on how two large open-source software projects (Google Chrome and Moodle) address the privacy requirements in our taxonomy through mining their issue reports. The paper discusses how the collected issues were classified, and presents the findings and insights generated from our study. Mining and classifying privacy requirements in issue reports can help organisations be aware of their state of compliance by identifying privacy requirements that have not been addressed in their software projects. The taxonomy can also trace back to regulations, standards and frameworks that the software projects have not complied with based on the identified privacy requirements. Comment: arXiv admin note: substantial text overlap with arXiv:2101.01298
Keywords	Computer Science - Cryptography and Security ; Computer Science - Software Engineering
Subject code	303 ; 005
Publishing date	2021-12-27
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Mining business rules from business process model repositories

Polpinij, Jantima / Dam, Hoa Khanh / Ghose, Aditya

Business process management journal Vol. 21, No. 4 , p. 820-836

2015 Volume 21, Issue 4, Page(s) 820–836

Author's details	Jantima Polpinij; Aditya Ghose and Hoa Khanh Dam
Keywords	Information management ; Process management ; Software engineering ; Business process redesign ; Knowledge management ; Process modelling
Language	English
Size	graph. Darst.
Publisher	Emerald
Publishing place	Bradford
Document type	Article
ZDB-ID	1379961-7 ; 2014421-0
ISSN	1463-7154
ISSN	1463-7154
Database	ECONomics Information System

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Book ; Online: A Value-based Trust Assessment Model for Multi-agent Systems

Chhogyal, Kinzang / Nayak, Abhaya / Ghose, Aditya / Dam, Hoa Khanh

2019

Abstract: An agent's assessment of its trust in another agent is commonly taken to be a measure of the reliability/predictability of the latter's actions. It is based on the trustor's past observations of the behaviour of the trustee and requires no knowledge of ... ...

Abstract	An agent's assessment of its trust in another agent is commonly taken to be a measure of the reliability/predictability of the latter's actions. It is based on the trustor's past observations of the behaviour of the trustee and requires no knowledge of the inner-workings of the trustee. However, in situations that are new or unfamiliar, past observations are of little help in assessing trust. In such cases, knowledge about the trustee can help. A particular type of knowledge is that of values - things that are important to the trustor and the trustee. In this paper, based on the premise that the more values two agents share, the more they should trust one another, we propose a simple approach to trust assessment between agents based on values, taking into account if agents trust cautiously or boldly, and if they depend on others in carrying out a task.
Keywords	Computer Science - Artificial Intelligence ; Computer Science - Multiagent Systems
Subject code	006
Publishing date	2019-05-30
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Adversarial Patch Generation for Automated Program Repair

Alhefdhi, Abdulaziz / Dam, Hoa Khanh / Le-Cong, Thanh / Le, Bach / Ghose, Aditya

2020

Abstract: Automated Program Repair has attracted significant research in recent years, leading to diverse techniques that focus on two main directions: search-based and semantic-based program repair. The former techniques often face challenges due to the vast ... ...

Abstract	Automated Program Repair has attracted significant research in recent years, leading to diverse techniques that focus on two main directions: search-based and semantic-based program repair. The former techniques often face challenges due to the vast search space, resulting in difficulties in identifying correct solutions, while the latter approaches are constrained by the capabilities of the underlying semantic analyser, limiting their scalability. In this paper, we propose NEVERMORE, a novel learning-based mechanism inspired by the adversarial nature of bugs and fixes. NEVERMORE is built upon the Generative Adversarial Networks architecture and trained on historical bug fixes to generate repairs that closely mimic human-produced fixes. Our empirical evaluation on 500 real-world bugs demonstrates the effectiveness of NEVERMORE in bug-fixing, generating repairs that match human fixes for 21.2% of the examined bugs. Moreover, we evaluate NEVERMORE on the Defects4J dataset, where our approach generates repairs for 4 bugs that remained unresolved by state-of-the-art baselines. NEVERMORE also fixes another 8 bugs which were only resolved by a subset of these baselines. Finally, we conduct an in-depth analysis of the impact of input and training styles on NEVERMORE's performance, revealing where the chosen style influences the model's bug-fixing capabilities.
Keywords	Computer Science - Software Engineering
Subject code	006
Publishing date	2020-12-20
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: First-Stage Development and Validation of a Web-Based Automated Dietary Modeling Tool: Using Constraint Optimization Techniques to Streamline Food Group and Macronutrient Focused Dietary Prescriptions for Clinical Trials.

Probst, Yasmine / Morrison, Evan / Sullivan, Emma / Dam, Hoa Khanh

Journal of medical Internet research

2016 Volume 18, Issue 7, Page(s) e190

Abstract: Background: Standardizing the background diet of participants during a dietary randomized controlled trial is vital to trial outcomes. For this process, dietary modeling based on food groups and their target servings is employed via a dietary ... ...

Abstract	Background: Standardizing the background diet of participants during a dietary randomized controlled trial is vital to trial outcomes. For this process, dietary modeling based on food groups and their target servings is employed via a dietary prescription before an intervention, often using a manual process. Partial automation has employed the use of linear programming. Validity of the modeling approach is critical to allow trial outcomes to be translated to practice. Objective: This paper describes the first-stage development of a tool to automatically perform dietary modeling using food group and macronutrient requirements as a test case. The Dietary Modeling Tool (DMT) was then compared with existing approaches to dietary modeling (manual and partially automated), which were previously available to dietitians working within a dietary intervention trial. Methods: Constraint optimization techniques were implemented to determine whether nonlinear constraints are best suited to the development of the automated dietary modeling tool using food composition and food consumption data. Dietary models were produced and compared with a manual Microsoft Excel calculator, a partially automated Excel Solver approach, and the automated DMT that was developed. Results: The web-based DMT was produced using nonlinear constraint optimization, incorporating estimated energy requirement calculations, nutrition guidance systems, and the flexibility to amend food group targets for individuals. Percentage differences between modeling tools revealed similar results for the macronutrients. Polyunsaturated fatty acids and monounsaturated fatty acids showed greater variation between tools (practically equating to a 2-teaspoon difference), although it was not considered clinically significant when the whole diet, as opposed to targeted nutrients or energy requirements, were being addressed. Conclusions: Automated modeling tools can streamline the modeling process for dietary intervention trials ensuring consistency of the background diets, although appropriate constraints must be used in their development to achieve desired results. The DMT was found to be a valid automated tool producing similar results to tools with less automation. The results of this study suggest interchangeability of the modeling approaches used, although implementation should reflect the requirements of the dietary intervention trial in which it is used.
MeSH term(s)	Diet ; Diet Therapy ; Dietary Carbohydrates ; Dietary Fats ; Dietary Proteins ; Energy Intake ; Feeding Behavior ; Food ; Humans ; Internet ; Linear Models ; Nutritional Requirements ; Randomized Controlled Trials as Topic ; Reference Standards
Chemical Substances	Dietary Carbohydrates ; Dietary Fats ; Dietary Proteins
Language	English
Publishing date	2016-07-28
Publishing country	Canada
Document type	Journal Article ; Validation Studies
ZDB-ID	2028830-X
ISSN	1438-8871 ; 1439-4456
ISSN (online)	1438-8871
ISSN	1439-4456
DOI	10.2196/jmir.5459
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: Towards effective AI-powered agile project management

Dam, Hoa Khanh / Tran, Truyen / Grundy, John / Ghose, Aditya / Kamei, Yasutaka

2018

Abstract: The rise of Artificial intelligence (AI) has the potential to significantly transform the practice of project management. Project management has a large socio-technical element with many uncertainties arising from variability in human aspects e.g., ... ...

Abstract	The rise of Artificial intelligence (AI) has the potential to significantly transform the practice of project management. Project management has a large socio-technical element with many uncertainties arising from variability in human aspects e.g., customers' needs, developers' performance and team dynamics. AI can assist project managers and team members by automating repetitive, high-volume tasks to enable project analytics for estimation and risk prediction, providing actionable recommendations, and even making decisions. AI is potentially a game changer for project management in helping to accelerate productivity and increase project success rates. In this paper, we propose a framework where AI technologies can be leveraged to offer support for managing agile projects, which have become increasingly popular in the industry. Comment: In Proceedings of International Conference on Software Engineering (ICSE 2019), (To appear), NIER track, May 2019 (Montreal, Canada)
Keywords	Computer Science - Software Engineering ; Computer Science - Artificial Intelligence
Subject code	690
Publishing date	2018-12-26
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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