— A methodology is presented which en-ables the specification and synthesis of software tools to ... more — A methodology is presented which en-ables the specification and synthesis of software tools to aid in plant and controller modeling for multi-domain (electrical, mechanical, hydraulic, and thermal) physical systems. The methodology is based on meta-modeling and graph rewriting. The plant is modeled in a domain-specific formalism called
Abstract. Large and complex meta-models such as those of Uml and its profiles are growing due to ... more Abstract. Large and complex meta-models such as those of Uml and its profiles are growing due to modelling and inter-operability needs of numerous stakeholders. The complexity of such meta-models has led to coining of the term meta-muddle. Individual users often exercise only a small view of a meta-muddle for tasks ranging from model creation to construction of model transformations. What is the effective meta-model that represents this view? We present a flexible meta-model pruning algorithm and tool to extract effective meta-models from a meta-muddle. We use the notion of model typing for meta-models to verify that the algorithm generates a super-type of the large meta-model representing the meta-muddle. This implies that all programs written using the effective meta-model will work for the meta-muddle hence preserving backward compatibility. All instances of the effective meta-model are also instances of the meta-muddle. We illustrate how pruning the original Uml metamodel produc...
— A methodology is presented which enables the specification and synthesis of software tools to a... more — A methodology is presented which enables the specification and synthesis of software tools to aid in plant and controller modeling for multi-domain (electrical, mechanical, hydraulic, and thermal) physical systems. The methodology is based on meta-modeling and graph rewriting. The plant is modeled in a domain-specific formalism called
Abstract. In Model Driven Engineering a model is a graph of objects that conforms to a meta-model... more Abstract. In Model Driven Engineering a model is a graph of objects that conforms to a meta-model and a set of constraints. The meta-model and the constraints declaratively restrict models to a valid set. Models are used to represent the state and behaviour of software systems. They are specified in visual modelling environments or automatically synthesized for program testing. In such applications, a modeller is interested in specifying a partial model or a set of partial models which has a structure and associated properties that interests him/her. Completing a partial model manually can be an extremely tedious or an undecidable task since the modeller has to satisfy tightly-coupled and arbitrary constraints. We identify this to be a problem and present a methodology to solve (if a solution can be found within certain time bounds) it using constraint logic programming. We present a transformation from a partial model, its meta-model, and additional constraints to a constraint logi...
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence
Obstructive sleep apnea is a serious sleep disorder that affects an estimated one billion adults ... more Obstructive sleep apnea is a serious sleep disorder that affects an estimated one billion adults worldwide. It causes breathing to repeatedly stop and start during sleep which over years increases the risk of hypertension, heart disease, stroke, Alzheimer's, and cancer. In this demo, we present Yolo4Apnea a deep learning system extending You Only Look Once (Yolo) system to detect sleep apnea events from abdominal breathing patterns in real-time enabling immediate awareness and action. Abdominal breathing is measured using a respiratory inductance plethysmography sensor worn around the stomach. The source code is available at https://github.com/simula-vias/Yolo4Apnea
Journal of Computational Methods in Sciences and Engineering
SK Sen a,∗ and Sagar Sen b a Department of Mathematical Sciences, Florida Institute of Technology... more SK Sen a,∗ and Sagar Sen b a Department of Mathematical Sciences, Florida Institute of Technology, 150 West University Boulevard, Melbourne, Florida 32901-6975, USA b Modeling, Simulation and Design Laboratory, School of Computer Science, McGill ...
There is a long-standing challenge to narrow the gap between software engineering research and in... more There is a long-standing challenge to narrow the gap between software engineering research and industry practice, to align their interests and realize true synergies between the two communities. Some difficulties to this challenge include mismatched agendas, priorities and expectations from the research collaboration on both sides. To overcome these difficulties, an initial step is to gain a clearer understanding of collaboration challenges from both perspectives. With this goal in mind, we organized the 5th International Workshop on Software Engineering Research and Industrial Practice, collocated with the International Conference on Software Engineering 2018. The workshop featured two keynote talks, one from industry and one from academia, followed by paper presentations and a round-table discussion session. Here we summarize experiences shared by the keynotes from industry and academia, along with findings from paper presentations and overall discussions by workshop participants ...
Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, Jan 28, 2017
Background: Privacy of information is an increasing concern with the availability of large amount... more Background: Privacy of information is an increasing concern with the availability of large amounts of data from many individuals. Even when access to data is heavily controlled, and the data shared with researchers contain no personal identifying information, there is a possibility of reidentifying individuals. To avoid reidentification, several anonymization protocols are available. These include categorizing variables into broader categories to ensure more than one individual in each category, such as k-anonymization, as well as protocols aimed at adding noise to the data. However, data custodians rarely assess reidentification risks.Methods: We assessed the reidentification risk of a large realistic dataset based on screening data from over 5 million records on 0.9 million women in the Norwegian Cervical Cancer Screening Program, before and after we used old and new techniques of adding noise (fuzzification) of the data.Results: Categorizing date variables (applying k-anonymizati...
International journal of medical informatics, Jul 1, 2017
In this paper, we propose a technique for improving anonymity in screening program databases to i... more In this paper, we propose a technique for improving anonymity in screening program databases to increase the privacy for the participants in these programs. The data generated by the invitation process (screening centre, appointment date) is often made available to researchers for medical research and for evaluation and improvement of the screening program. This information, combined with other personal quasi-identifiers such as the ZIP code, gender or age, can pose a risk of disclosing the identity of the individuals participating in the program, and eventually their test results. We present two algorithms that produce a set of screening appointments that aim to increase anonymity of the resulting dataset. The first one, based on the constraint programming paradigm, defines the optimal appointments, while the second one is a suboptimal heuristic algorithm that can be used with real size datasets. The level of anonymity is measured using the new concept of generalized k-anonymity, w...
— A methodology is presented which en-ables the specification and synthesis of software tools to ... more — A methodology is presented which en-ables the specification and synthesis of software tools to aid in plant and controller modeling for multi-domain (electrical, mechanical, hydraulic, and thermal) physical systems. The methodology is based on meta-modeling and graph rewriting. The plant is modeled in a domain-specific formalism called
Abstract. Large and complex meta-models such as those of Uml and its profiles are growing due to ... more Abstract. Large and complex meta-models such as those of Uml and its profiles are growing due to modelling and inter-operability needs of numerous stakeholders. The complexity of such meta-models has led to coining of the term meta-muddle. Individual users often exercise only a small view of a meta-muddle for tasks ranging from model creation to construction of model transformations. What is the effective meta-model that represents this view? We present a flexible meta-model pruning algorithm and tool to extract effective meta-models from a meta-muddle. We use the notion of model typing for meta-models to verify that the algorithm generates a super-type of the large meta-model representing the meta-muddle. This implies that all programs written using the effective meta-model will work for the meta-muddle hence preserving backward compatibility. All instances of the effective meta-model are also instances of the meta-muddle. We illustrate how pruning the original Uml metamodel produc...
— A methodology is presented which enables the specification and synthesis of software tools to a... more — A methodology is presented which enables the specification and synthesis of software tools to aid in plant and controller modeling for multi-domain (electrical, mechanical, hydraulic, and thermal) physical systems. The methodology is based on meta-modeling and graph rewriting. The plant is modeled in a domain-specific formalism called
Abstract. In Model Driven Engineering a model is a graph of objects that conforms to a meta-model... more Abstract. In Model Driven Engineering a model is a graph of objects that conforms to a meta-model and a set of constraints. The meta-model and the constraints declaratively restrict models to a valid set. Models are used to represent the state and behaviour of software systems. They are specified in visual modelling environments or automatically synthesized for program testing. In such applications, a modeller is interested in specifying a partial model or a set of partial models which has a structure and associated properties that interests him/her. Completing a partial model manually can be an extremely tedious or an undecidable task since the modeller has to satisfy tightly-coupled and arbitrary constraints. We identify this to be a problem and present a methodology to solve (if a solution can be found within certain time bounds) it using constraint logic programming. We present a transformation from a partial model, its meta-model, and additional constraints to a constraint logi...
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence
Obstructive sleep apnea is a serious sleep disorder that affects an estimated one billion adults ... more Obstructive sleep apnea is a serious sleep disorder that affects an estimated one billion adults worldwide. It causes breathing to repeatedly stop and start during sleep which over years increases the risk of hypertension, heart disease, stroke, Alzheimer's, and cancer. In this demo, we present Yolo4Apnea a deep learning system extending You Only Look Once (Yolo) system to detect sleep apnea events from abdominal breathing patterns in real-time enabling immediate awareness and action. Abdominal breathing is measured using a respiratory inductance plethysmography sensor worn around the stomach. The source code is available at https://github.com/simula-vias/Yolo4Apnea
Journal of Computational Methods in Sciences and Engineering
SK Sen a,∗ and Sagar Sen b a Department of Mathematical Sciences, Florida Institute of Technology... more SK Sen a,∗ and Sagar Sen b a Department of Mathematical Sciences, Florida Institute of Technology, 150 West University Boulevard, Melbourne, Florida 32901-6975, USA b Modeling, Simulation and Design Laboratory, School of Computer Science, McGill ...
There is a long-standing challenge to narrow the gap between software engineering research and in... more There is a long-standing challenge to narrow the gap between software engineering research and industry practice, to align their interests and realize true synergies between the two communities. Some difficulties to this challenge include mismatched agendas, priorities and expectations from the research collaboration on both sides. To overcome these difficulties, an initial step is to gain a clearer understanding of collaboration challenges from both perspectives. With this goal in mind, we organized the 5th International Workshop on Software Engineering Research and Industrial Practice, collocated with the International Conference on Software Engineering 2018. The workshop featured two keynote talks, one from industry and one from academia, followed by paper presentations and a round-table discussion session. Here we summarize experiences shared by the keynotes from industry and academia, along with findings from paper presentations and overall discussions by workshop participants ...
Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, Jan 28, 2017
Background: Privacy of information is an increasing concern with the availability of large amount... more Background: Privacy of information is an increasing concern with the availability of large amounts of data from many individuals. Even when access to data is heavily controlled, and the data shared with researchers contain no personal identifying information, there is a possibility of reidentifying individuals. To avoid reidentification, several anonymization protocols are available. These include categorizing variables into broader categories to ensure more than one individual in each category, such as k-anonymization, as well as protocols aimed at adding noise to the data. However, data custodians rarely assess reidentification risks.Methods: We assessed the reidentification risk of a large realistic dataset based on screening data from over 5 million records on 0.9 million women in the Norwegian Cervical Cancer Screening Program, before and after we used old and new techniques of adding noise (fuzzification) of the data.Results: Categorizing date variables (applying k-anonymizati...
International journal of medical informatics, Jul 1, 2017
In this paper, we propose a technique for improving anonymity in screening program databases to i... more In this paper, we propose a technique for improving anonymity in screening program databases to increase the privacy for the participants in these programs. The data generated by the invitation process (screening centre, appointment date) is often made available to researchers for medical research and for evaluation and improvement of the screening program. This information, combined with other personal quasi-identifiers such as the ZIP code, gender or age, can pose a risk of disclosing the identity of the individuals participating in the program, and eventually their test results. We present two algorithms that produce a set of screening appointments that aim to increase anonymity of the resulting dataset. The first one, based on the constraint programming paradigm, defines the optimal appointments, while the second one is a suboptimal heuristic algorithm that can be used with real size datasets. The level of anonymity is measured using the new concept of generalized k-anonymity, w...
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