Gunjan Mansingh | The University of the West Indies, Mona, Jamaica (original) (raw)

Papers by Gunjan Mansingh

IGI Global eBooks, 2018

Knowledge discovery and data-mining techniques have the potential to provide insights into data t... more Knowledge discovery and data-mining techniques have the potential to provide insights into data that can improve decision making. This paper explores the use of data mining to extract patterns from data in the domain of social welfare. It discusses the application of the Integrated Knowledge Discovery and Data Mining process model (IKDDM) a social welfare programme in Jamaica. Further, it demonstrates how the knowledge acquired from the data is used to develop a knowledge driven decision support system (DSS) in the PATH CCT programme. This system was successfully tested in the domain showing over 94% accuracy in the comparative decisions produced.

Springer eBooks, Dec 20, 2013

Knowledge management has been dependent largely on technologies that are used to manage data and ... more Knowledge management has been dependent largely on technologies that are used to manage data and information. However, it is widely accepted that there is an important distinction between knowledge and data and information and until there is a focus on building strategies and technologies specific to knowledge management, the full potential of knowledge cannot be realized. Within an organization knowledge resides in numerous sources of different types such as human experts, processes, and data stores. Therefore the development of the specific technologies should focus on the management of this knowledge within these different sources. Many of these technologies need access to the knowledge of the domain which can be formally represented using an ontology. In this chapter we describe three ontology-driven knowledge technologies and discuss how they can be beneficial in harnessing knowledge in these varied sources.

Knowledge Management Research & Practice, Mar 1, 2009

Organizational knowledge exists in different types of knowledge retainers. Efforts are being made... more Organizational knowledge exists in different types of knowledge retainers. Efforts are being made to preserve this knowledge because of its value to the organization. In this paper we present a methodology for codifying the knowledge of a domain. This methodology is based on an ontology for the domain in question, from which different types of knowledge items are extracted. These knowledge items represent the different types of knowing that are embedded in the organization's structure and its processes. From an analysis of a process instance described in the ontology, different knowledge items can be extracted and represented as knowledge maps. These maps represent the internal competencies of the organization as they relate to certain processes and hence they can be used to provide inputs in the decision-making process, for example, knowledge process outsourcing decisions. The purpose of this paper is to present an ontology-driven methodology for extracting different knowledge items and representing them as knowledge maps.

Health Systems, Mar 1, 2016

Sickle cell disease (SCD) is the most common single-gene disorder worldwide and has multiple and ... more Sickle cell disease (SCD) is the most common single-gene disorder worldwide and has multiple and variable manifestations. The many medical complications associated with SCD such as acute chest syndrome and painful crises, along with a lack of normal functioning, may lead to various psychosocial problems such as depression, loneliness and impaired quality of life (QOL). A few studies have sought to examine the relationships between demographics, disease severity, depression, loneliness and the QOL of patients with SCD. In this paper we apply an integrated knowledge discovery and data mining (IKDDM) process to explore the factors that impact the QOL of patients with SCD in Jamaica to explicate knowledge that can be used by medical professionals. Following the IKDDM process provides several benefits: (1) it ensures that adequate experimentation is done to ensure that the best model will be generated and (2) it provides guidance in generating and evaluating models. We use different data mining techniques such as Decision Trees Induction, Regression and Regression Splines to analyze the data and multiple performance measures to evaluate the models in order to identify the best set of models to present to the medical professionals. This allows the medical professionals to select model(s) that will assist them in the decision-making process. The results of this study confirm prior hypotheses regarding the variables predictive of the QOL of SCD patients and additionally provide new insights by identifying the values for these variables.

British Journal of Sports Medicine, Feb 1, 2006

To analyse injuries in West Indies Cricket and compare them with those of other cricket playing n... more To analyse injuries in West Indies Cricket and compare them with those of other cricket playing nations. Methods: Injuries between June 2003 and December 2004 were surveyed prospectively in all major matches of the West Indies Cricket Board. Results: Most injuries occurred in the West Indies Test and one day international teams. Mean match injury incidence was 48.7 per 10 000 player-hours in Test cricket, and 40.6 per 10 000 player-hours in one day international cricket, with injury prevalence of 11.3% and 8.1% respectively. In domestic cricket, the match injury incidence was 13.9 per 10 000 player-hours for first class cricket, and 25.4 per 10 000 playerhours in one day domestic competitions. There were more injuries on tour for the West Indies team than at home. The batsmen and fast bowlers sustained 80% of injuries, with many leading to long absence from the game, although many of these injuries were sustained while fielding. Most injuries were of the phalanges (22%) and the lumbar spine (20%) sustained mainly while fielding (including catching) and fast bowling respectively. Conclusions: Injuries in West Indies cricket may be reduced by (a) early detection and management of injuries on tour, (b) attention to fielding and catching techniques, and (c) monitoring of young fast bowlers.

arXiv (Cornell University), Oct 15, 2021

Mobile health systems in recent times, have notably improved the healthcare sector by empowering ... more Mobile health systems in recent times, have notably improved the healthcare sector by empowering patients to actively participate in their health, and by facilitating access to healthcare professionals. Effective operation of these mobile systems nonetheless, requires high level of intelligence and expertise implemented in the form of decision support systems (DSS). However, common challenges in the implementation include generalization and reliability, due to the dynamics and incompleteness of information presented to the inference models. In this paper, we advance the use of ad hoc mobile decision support system to monitor and detect triggers and early symptoms of respiratory distress provoked by strenuous physical exertion. The focus is on the application of certainty theory to model inexact reasoning by the mobile monitoring system. The aim is to develop a mobile tool to assist patients in managing their conditions, and to provide objective clinical data to aid physicians in the screening, diagnosis, and treatment of the respiratory ailments. We present the proposed model architecture and then describe an application scenario in a clinical setting. We also show implementation of an aspect of the system that enables patients in the self-management of their conditions.

SSRN Electronic Journal

Creative expression, and authorship of creative works, has long been associated with humans. Arti... more Creative expression, and authorship of creative works, has long been associated with humans. Artificial Intelligence (AI) algorithms generally associated with routine tasks, are now being used in the creative industries. While human effort is still necessary to perfect creative works done by technology, ongoing algorithmic improvements and adaptations have further advanced the creative capabilities of AI technology. If humans are unable to decipher whether a painting, a piece of music or a literary work was created by humans or an algorithm then it potentially opens a Pandora's Box. What therefore are the legal implications in the creative space when an algorithm passes the Turing test, i.e. when a human is unable to tell whether an output (artistic work) was generated by a human or a machine? In July 2021, workshops were held in Jamaica with stakeholders from the creative industries, the technology industry and legal practitioners to determine their knowledge of capabilities of AI in the creative industries and their perspectives on the possible legal implications of a creator not being human. This paper considers the legal significance of the presumption that, creativity and authorship, tenets on which intellectual property (IP) protection is generally premised, emanate from a person. Arguably, the dialectic is not whether AI has supplanted human creativity, or the difficulty with being able to distinguish a work created by a human or autonomously by AI. The polemic posed is, what, if any, legislative or regulatory accommodation is needed to address

Integrated series on information systems, Dec 20, 2013

In this chapter we provide an overview on knowledge management (KM) and knowledge management syst... more In this chapter we provide an overview on knowledge management (KM) and knowledge management systems. Foundational concepts that are relevant to the other chapters are discussed. This chapter along with the other chapters aims to provide guidance to researchers and practitioners who are looking to address KM in developing countries.

Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics, 2017

This paper explores the capabilities of mobile phones to distinguish sound-related symptoms of re... more This paper explores the capabilities of mobile phones to distinguish sound-related symptoms of respiratory conditions using machine learning algorithms. The classification tool is modeled after some standard set of temporal and spectral features used in vocal and lung sound analysis. These features are extracted from recorded sounds and then fed into machine learning algorithms to train the mobile system. Random Forest, Support Vector Machine (SVM), and k-Nearest Neighbour (kNN) classifiers were evaluated with an overall accuracy of 86.7%, 75.8%, and 88.9% respectively. The appreciable performance of these classifiers on a mobile phone shows smartphone as an alternate tool for recognition and discrimination of respiratory symptoms in real-time scenarios.

Proceedings of the 50th ACM Technical Symposium on Computer Science Education, 2019

As computing enrollments have grown in the last decade there have been anecdotal claims from facu... more As computing enrollments have grown in the last decade there have been anecdotal claims from faculty that the discipline has attracted weaker students. To the best of our knowledge the only paper that has studied, and debunked, this claim has been based on data from an exclusive North American university. In this paper we examine data from six courses drawn taught over a 3 year period at a public university in a developing country. We find that in the case of the CS1 course, the distribution of student grades has fluctuated over this period. In addition, courses in object-oriented programming, networking, algorithms and discrete mathematics have also shown variation in student grades. We provide discussion as to why the grades in the courses show variation. We also explain why our findings differ from previous claims of stability in student grades.

Integrated Series in Information Systems, 2014

The use of general descriptive names, registered names, trademarks, service marks, etc. in this p... more The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specifi c statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein.

ArXiv, 2021

Advances in mobile computing have paved the way for the development of several health application... more Advances in mobile computing have paved the way for the development of several health applications using Smartphone as a platform for data acquisition, analysis and presentation. Such areas where m-health systems have been extensively deployed include monitoring of long-term health conditions like Cardio-Vascular Diseases and pulmonary disorders, as well as detection of changes from baseline measurements of such conditions. Asthma is one of the respiratory conditions with growing concern across the globe due to the economic, social and emotional burden associated with the ailment. The management and control of asthma can be improved by consistent monitoring of the condition in real-time since attack could occur anytime and anywhere. This paper proposes the use of smartphone equipped with built-in sensors, to capture and analyse early symptoms of asthma triggered by exercise. The system design is based on Decision Support System (DSS) techniques for measuring and analysing the level ...

Business Intelligence for Small and Medium-Sized Enterprises, 2018

Business Intelligence (BI) has become a strategic initiative of many organizations and successful... more Business Intelligence (BI) has become a strategic initiative of many organizations and successful BI implementations have generated significant increases in revenue and cost savings, however, failure rates are also very high and some organisations are cautious to invest in BI initiatives. One of the reasons for this high failure rate is that traditional BI methods are not suited to all organizations; they are seen by some as being too rigid and resource intensive. Additionally, the focus is often on localized rather than enterprise-wide analytics. This paper addresses these issues by proposing a BI methodology that integrates a number of existing techniques to support an agile, enterprise-wide perspective. This methodology provides a systematic and structured approach that is enterprise in reach yet agile in execution and generates a strategic BI Roadmap. It was evaluated using a case study and the agile and strategic focus was found to be extremely beneficial.

Business Intelligence for Small and Medium-Sized Enterprises, 2019

Decision making is a key activity for management in any organization, several decision making met... more Decision making is a key activity for management in any organization, several decision making methods including Multi Criteria Decision Making (MCDM) have been used to assist this process especially when the decision involves multiple stakeholders and multiple criteria. These methods, which evaluate each alternative by a set of criteria, tend to be subjective in nature. However, although they are subjective it should be ensured that the decisions makers have as much knowledge about the alternatives as is possible. This would include understanding all the consequences of each alternative and all the effects of these consequences. This requires a thorough understanding of the domain within which the decision is being made. We argue that an organizational ontology provides this understanding and propose a method for integrating an ontology into typical multi-criteria decision making techniques. The overall aim of this method is to improve the decision making process. We demonstrate the...

Business Intelligence for Small and Medium-Sized Enterprises, 2019

IGI Global eBooks, 2018

Knowledge discovery and data-mining techniques have the potential to provide insights into data t... more Knowledge discovery and data-mining techniques have the potential to provide insights into data that can improve decision making. This paper explores the use of data mining to extract patterns from data in the domain of social welfare. It discusses the application of the Integrated Knowledge Discovery and Data Mining process model (IKDDM) a social welfare programme in Jamaica. Further, it demonstrates how the knowledge acquired from the data is used to develop a knowledge driven decision support system (DSS) in the PATH CCT programme. This system was successfully tested in the domain showing over 94% accuracy in the comparative decisions produced.

Springer eBooks, Dec 20, 2013

Knowledge management has been dependent largely on technologies that are used to manage data and ... more Knowledge management has been dependent largely on technologies that are used to manage data and information. However, it is widely accepted that there is an important distinction between knowledge and data and information and until there is a focus on building strategies and technologies specific to knowledge management, the full potential of knowledge cannot be realized. Within an organization knowledge resides in numerous sources of different types such as human experts, processes, and data stores. Therefore the development of the specific technologies should focus on the management of this knowledge within these different sources. Many of these technologies need access to the knowledge of the domain which can be formally represented using an ontology. In this chapter we describe three ontology-driven knowledge technologies and discuss how they can be beneficial in harnessing knowledge in these varied sources.

Knowledge Management Research & Practice, Mar 1, 2009

Organizational knowledge exists in different types of knowledge retainers. Efforts are being made... more Organizational knowledge exists in different types of knowledge retainers. Efforts are being made to preserve this knowledge because of its value to the organization. In this paper we present a methodology for codifying the knowledge of a domain. This methodology is based on an ontology for the domain in question, from which different types of knowledge items are extracted. These knowledge items represent the different types of knowing that are embedded in the organization's structure and its processes. From an analysis of a process instance described in the ontology, different knowledge items can be extracted and represented as knowledge maps. These maps represent the internal competencies of the organization as they relate to certain processes and hence they can be used to provide inputs in the decision-making process, for example, knowledge process outsourcing decisions. The purpose of this paper is to present an ontology-driven methodology for extracting different knowledge items and representing them as knowledge maps.

Health Systems, Mar 1, 2016

Sickle cell disease (SCD) is the most common single-gene disorder worldwide and has multiple and ... more Sickle cell disease (SCD) is the most common single-gene disorder worldwide and has multiple and variable manifestations. The many medical complications associated with SCD such as acute chest syndrome and painful crises, along with a lack of normal functioning, may lead to various psychosocial problems such as depression, loneliness and impaired quality of life (QOL). A few studies have sought to examine the relationships between demographics, disease severity, depression, loneliness and the QOL of patients with SCD. In this paper we apply an integrated knowledge discovery and data mining (IKDDM) process to explore the factors that impact the QOL of patients with SCD in Jamaica to explicate knowledge that can be used by medical professionals. Following the IKDDM process provides several benefits: (1) it ensures that adequate experimentation is done to ensure that the best model will be generated and (2) it provides guidance in generating and evaluating models. We use different data mining techniques such as Decision Trees Induction, Regression and Regression Splines to analyze the data and multiple performance measures to evaluate the models in order to identify the best set of models to present to the medical professionals. This allows the medical professionals to select model(s) that will assist them in the decision-making process. The results of this study confirm prior hypotheses regarding the variables predictive of the QOL of SCD patients and additionally provide new insights by identifying the values for these variables.

British Journal of Sports Medicine, Feb 1, 2006

To analyse injuries in West Indies Cricket and compare them with those of other cricket playing n... more To analyse injuries in West Indies Cricket and compare them with those of other cricket playing nations. Methods: Injuries between June 2003 and December 2004 were surveyed prospectively in all major matches of the West Indies Cricket Board. Results: Most injuries occurred in the West Indies Test and one day international teams. Mean match injury incidence was 48.7 per 10 000 player-hours in Test cricket, and 40.6 per 10 000 player-hours in one day international cricket, with injury prevalence of 11.3% and 8.1% respectively. In domestic cricket, the match injury incidence was 13.9 per 10 000 player-hours for first class cricket, and 25.4 per 10 000 playerhours in one day domestic competitions. There were more injuries on tour for the West Indies team than at home. The batsmen and fast bowlers sustained 80% of injuries, with many leading to long absence from the game, although many of these injuries were sustained while fielding. Most injuries were of the phalanges (22%) and the lumbar spine (20%) sustained mainly while fielding (including catching) and fast bowling respectively. Conclusions: Injuries in West Indies cricket may be reduced by (a) early detection and management of injuries on tour, (b) attention to fielding and catching techniques, and (c) monitoring of young fast bowlers.

arXiv (Cornell University), Oct 15, 2021

Mobile health systems in recent times, have notably improved the healthcare sector by empowering ... more Mobile health systems in recent times, have notably improved the healthcare sector by empowering patients to actively participate in their health, and by facilitating access to healthcare professionals. Effective operation of these mobile systems nonetheless, requires high level of intelligence and expertise implemented in the form of decision support systems (DSS). However, common challenges in the implementation include generalization and reliability, due to the dynamics and incompleteness of information presented to the inference models. In this paper, we advance the use of ad hoc mobile decision support system to monitor and detect triggers and early symptoms of respiratory distress provoked by strenuous physical exertion. The focus is on the application of certainty theory to model inexact reasoning by the mobile monitoring system. The aim is to develop a mobile tool to assist patients in managing their conditions, and to provide objective clinical data to aid physicians in the screening, diagnosis, and treatment of the respiratory ailments. We present the proposed model architecture and then describe an application scenario in a clinical setting. We also show implementation of an aspect of the system that enables patients in the self-management of their conditions.

SSRN Electronic Journal

Creative expression, and authorship of creative works, has long been associated with humans. Arti... more Creative expression, and authorship of creative works, has long been associated with humans. Artificial Intelligence (AI) algorithms generally associated with routine tasks, are now being used in the creative industries. While human effort is still necessary to perfect creative works done by technology, ongoing algorithmic improvements and adaptations have further advanced the creative capabilities of AI technology. If humans are unable to decipher whether a painting, a piece of music or a literary work was created by humans or an algorithm then it potentially opens a Pandora's Box. What therefore are the legal implications in the creative space when an algorithm passes the Turing test, i.e. when a human is unable to tell whether an output (artistic work) was generated by a human or a machine? In July 2021, workshops were held in Jamaica with stakeholders from the creative industries, the technology industry and legal practitioners to determine their knowledge of capabilities of AI in the creative industries and their perspectives on the possible legal implications of a creator not being human. This paper considers the legal significance of the presumption that, creativity and authorship, tenets on which intellectual property (IP) protection is generally premised, emanate from a person. Arguably, the dialectic is not whether AI has supplanted human creativity, or the difficulty with being able to distinguish a work created by a human or autonomously by AI. The polemic posed is, what, if any, legislative or regulatory accommodation is needed to address

Integrated series on information systems, Dec 20, 2013

In this chapter we provide an overview on knowledge management (KM) and knowledge management syst... more In this chapter we provide an overview on knowledge management (KM) and knowledge management systems. Foundational concepts that are relevant to the other chapters are discussed. This chapter along with the other chapters aims to provide guidance to researchers and practitioners who are looking to address KM in developing countries.

Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics, 2017

This paper explores the capabilities of mobile phones to distinguish sound-related symptoms of re... more This paper explores the capabilities of mobile phones to distinguish sound-related symptoms of respiratory conditions using machine learning algorithms. The classification tool is modeled after some standard set of temporal and spectral features used in vocal and lung sound analysis. These features are extracted from recorded sounds and then fed into machine learning algorithms to train the mobile system. Random Forest, Support Vector Machine (SVM), and k-Nearest Neighbour (kNN) classifiers were evaluated with an overall accuracy of 86.7%, 75.8%, and 88.9% respectively. The appreciable performance of these classifiers on a mobile phone shows smartphone as an alternate tool for recognition and discrimination of respiratory symptoms in real-time scenarios.

Proceedings of the 50th ACM Technical Symposium on Computer Science Education, 2019

As computing enrollments have grown in the last decade there have been anecdotal claims from facu... more As computing enrollments have grown in the last decade there have been anecdotal claims from faculty that the discipline has attracted weaker students. To the best of our knowledge the only paper that has studied, and debunked, this claim has been based on data from an exclusive North American university. In this paper we examine data from six courses drawn taught over a 3 year period at a public university in a developing country. We find that in the case of the CS1 course, the distribution of student grades has fluctuated over this period. In addition, courses in object-oriented programming, networking, algorithms and discrete mathematics have also shown variation in student grades. We provide discussion as to why the grades in the courses show variation. We also explain why our findings differ from previous claims of stability in student grades.

Integrated Series in Information Systems, 2014

The use of general descriptive names, registered names, trademarks, service marks, etc. in this p... more The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specifi c statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein.

ArXiv, 2021

Advances in mobile computing have paved the way for the development of several health application... more Advances in mobile computing have paved the way for the development of several health applications using Smartphone as a platform for data acquisition, analysis and presentation. Such areas where m-health systems have been extensively deployed include monitoring of long-term health conditions like Cardio-Vascular Diseases and pulmonary disorders, as well as detection of changes from baseline measurements of such conditions. Asthma is one of the respiratory conditions with growing concern across the globe due to the economic, social and emotional burden associated with the ailment. The management and control of asthma can be improved by consistent monitoring of the condition in real-time since attack could occur anytime and anywhere. This paper proposes the use of smartphone equipped with built-in sensors, to capture and analyse early symptoms of asthma triggered by exercise. The system design is based on Decision Support System (DSS) techniques for measuring and analysing the level ...

Business Intelligence for Small and Medium-Sized Enterprises, 2018

Business Intelligence (BI) has become a strategic initiative of many organizations and successful... more Business Intelligence (BI) has become a strategic initiative of many organizations and successful BI implementations have generated significant increases in revenue and cost savings, however, failure rates are also very high and some organisations are cautious to invest in BI initiatives. One of the reasons for this high failure rate is that traditional BI methods are not suited to all organizations; they are seen by some as being too rigid and resource intensive. Additionally, the focus is often on localized rather than enterprise-wide analytics. This paper addresses these issues by proposing a BI methodology that integrates a number of existing techniques to support an agile, enterprise-wide perspective. This methodology provides a systematic and structured approach that is enterprise in reach yet agile in execution and generates a strategic BI Roadmap. It was evaluated using a case study and the agile and strategic focus was found to be extremely beneficial.

Business Intelligence for Small and Medium-Sized Enterprises, 2019

Decision making is a key activity for management in any organization, several decision making met... more Decision making is a key activity for management in any organization, several decision making methods including Multi Criteria Decision Making (MCDM) have been used to assist this process especially when the decision involves multiple stakeholders and multiple criteria. These methods, which evaluate each alternative by a set of criteria, tend to be subjective in nature. However, although they are subjective it should be ensured that the decisions makers have as much knowledge about the alternatives as is possible. This would include understanding all the consequences of each alternative and all the effects of these consequences. This requires a thorough understanding of the domain within which the decision is being made. We argue that an organizational ontology provides this understanding and propose a method for integrating an ontology into typical multi-criteria decision making techniques. The overall aim of this method is to improve the decision making process. We demonstrate the...

Business Intelligence for Small and Medium-Sized Enterprises, 2019