Hoa Khanh Dam

Simultaneous nitrification/denitrification and trace organic contaminant (TrOC) removal by an anoxic-aerobic membrane bioreactor (MBR).

Simultaneous nitrification/denitrification and trace organic contaminant (TrOC) removal during wastewater treatment by an integrated anoxic-aerobic MBR was examined. A set of 30 compounds was selected to represent TrOCs that occur ubiquitously in domestic wastewater. The system achieved over 95% total organic carbon (TOC) and over 80% total nitrogen (TN) removal. In addition, 21 of the 30 TrOCs investigated here were removed by over 90%. Low oxidation reduction potential (i.e., anoxic/anaerobic) regimes were conducive to moderate to high (50% to 90%) removal of nine TrOCs. These included four pharmaceuticals and personal care products (primidone, metronidazole, triclosan, and amitriptyline), one steroid hormone (17β-estradiol-17-acetate), one industrial chemical (4-tert-octylphenol) and all three selected UV filters (benzophenone, oxybenzone, and octocrylene). Internal recirculation between the anoxic and aerobic bioreactors was essential for anoxic removal of remaining TrOCs. A major role of the aerobic MBR for TOC, TN, and TrOC removal was observed.

Supporting change propagation in UML models

A critical issue in software maintenance and evolution is change propagation: given a primary change that is made in order to meet a new or changed requirement, what additional, secondary, changes are needed? We have previously developed techniques for effectively supporting change propagation within design models of intelligent agent systems. In this paper, we propose how this approach is applied to support change propagation within UML design models. Our approach offers a number of advantages in terms of saving substantial time writing hard-coded rules, ensuring soundness and completeness, and at the same time capturing the cascading nature of change propagation. We will also present and discuss the results of an evaluation performed to assess the scalability of our approach.

An agent-oriented approach to change propagation in software maintenance

Software maintenance and evolution is a lengthy and expensive phase in the life cycle of a software system. In this paper we focus on the change propagation problem: given a primary change that is made in order to meet a new or changed requirement, what additional, secondary, changes are needed? We propose a novel, agent-oriented, approach that works by repairing violations of desired consistency rules in a design model. Such consistency constraints are specified using the Object Constraint Language (OCL) and the Unified Modelling Language (UML) metamodel, which form the key inputs to our change propagation framework. The underlying change propagation mechanism of our framework is based on the well-known Belief-Desire-Intention (BDI) agent architecture. Our approach represents change options for repairing inconsistencies using event-triggered plans, as is done in BDI agent platforms. This naturally reflects the cascading nature of change propagation, where each change (primary or secondary) can require further changes to be made. We also propose a new method for generating repair plans from OCL consistency constraints. Furthermore, a given inconsistency will typically have a number of repair plans that could be used to restore consistency, and we propose a mechanism for semi-automatically selecting between alternative repair plans. This mechanism, which is based on a notion of cost, takes into account cascades (where fixing the violation of a constraint breaks another constraint), and synergies between constraints (where fixing the violation of a constraint also fixes another violated constraint). Finally, we report on an evaluation of the approach, covering effectiveness, efficiency and scalability.

Towards a next-generation AOSE methodology

Numerous methodologies for developing agent-based systems have been proposed in the literature. This proliferation creates a challenge to practitioners who need to select a methodology to adopt. This situation is analogous to that of object-oriented methodologies and notations pre-UML, and we argue that the time is ripe to begin the development of a next generation agent-oriented software engineering (AOSE) methodology, leading ultimately towards a unified AOSE methodology. This paper proposes process and models for a next generation AOSE methodology. Our proposal is based on a comparative analysis of seven prominent AOSE methodologies, which identified strengths, weaknesses, commonalities and differences.

Strategic alignment of business processes

Strategic alignment is a mechanism by which an organization can visualize the relationship between its business processes and strategies. It enables organizational decision makers to collect meaningful insights based on their current processes. Currently it is difficult to show the sustainability of an organization and to determine an optimal set of processes that are required for realizing strategies. Further, there is not a general framework for strategic alignment that can ease this problem. In this article, we propose such a general framework for strategic alignment, which helps develop a clear understanding of the relationships between strategies and business processes. The framework gives organizations an understanding of the relationship between a set of processes and the realization of a set of strategies; it also shows the optimal set of processes that can achieve these strategies.

Supporting Change Propagation in the Evolution of Enterprise Architectures

Enterprise Architecture (EA) models the whole vision of an organisation in various aspects regarding both business processes and information technology resources. As the organisation grows, the architecture governing its systems and processes must also evolve to meet with the demands of the business environment. In this context, a critical issue is change propagation: given a set of primary changes that have been made to the EA model, what additional secondary changes are needed to maintain consistency across multiple levels of the EA. This paper proposes an enterprise architectural description language, namely Change Aware Hierarchical EA, integrated with a framework to support change propagation within an EA model. The core part of our change propagation framework is a new method for generating interactive repair plans from Alloy consistency rules that constrain the EA model.

On Formalizing Inter-process Relationships

Most medium to large organizations support large collections of process designs, often stored in business process repositories. These processes are often inter-dependent. Managing such large collections of processes is not a trivial task. We argue that formalizing and establishing inter-process relationships play a critical role in that task leading to a machinery approach in the process repository management. We consider and propose three kinds of such relationships, namely part-whole, inter-operation and generalization-specialization, including their formal definitions, permitting us to develop a machinery approach. Analysis of the relationships relies on the semantically effects annotated process model in BPMN. This paper presents a rigorous approach to assist the designer to establish inter-process relationships in a process repository.

Predicting Delays in Software Projects Using Networked Classification (T)

Software projects have a high risk of cost and schedule overruns, which has been a source of concern for the software engineering community for a long time. One of the challenges in software project management is to make reliable prediction of delays in the context of constant and rapid changes inherent in software projects. This paper presents a novel approach to providing automated support for project managers and other decision makers in predicting whether a subset of software tasks (among the hundreds to thousands of ongoing tasks) in a software project have a risk of being delayed. Our approach makes use of not only features specific to individual software tasks (i.e. local data) -- as done in previous work -- but also their relationships (i.e. networked data). In addition, using collective classification, our approach can simultaneously predict the degree of delay for a group of related tasks. Our evaluation results show a significant improvement over traditional approaches which perform classification on each task independently: achieving 46% -- 97% precision (49% improved), 46% -- 97% recall (28% improved), 56% -- 75% F-measure (39% improved), and 78% -- 95% Area Under the ROC Curve (16% improved).

Characterization and prediction of issue-related risks in software projects

Identifying risks relevant to a software project and planning measures to deal with them are critical to the success of the project. Current practices in risk assessment mostly rely on high-level, generic guidance or the subjective judgements of experts. In this paper, we propose a novel approach to risk assessment using historical data associated with a software project. Specifically, our approach identifies patterns of past events that caused project delays, and uses this knowledge to identify risks in the current state of the project. A set of risk factors characterizing “risky” software tasks (in the form of issues) were extracted from five open source projects: Apache, Duraspace, JBoss, Moodle, and Spring. In addition, we performed feature selection using a sparse logistic regression model to select risk factors with good discriminative power. Based on these risk factors, we built predictive models to predict if an issue will cause a project delay. Our predictive models are able to predict both the risk impact (i.e. the extend of the delay) and the likelihood of a risk occurring. The evaluation results demonstrate the effectiveness of our predictive models, achieving on average 48%-81% precision, 23%-90% recall, 29%-71% F-measure, and 70%-92% Area Under the ROC Curve. Our predictive models also have low error rates: 0.39-0.75 for Macro-averaged Mean Cost-Error and 0.7-1.2 for Macro-averaged Mean Absolute Error.

Supporting Change Propagation in the Maintenance and Evolution of Service-Oriented Architectures

As Service-Oriented Architecture (SOA) continues to be broadly adopted, the maintenance and evolution of service-oriented systems become a growing issue. Maintenance and evolution are inevitable activities since almost all systems that are useful and successful stimulate user-generated requests for change and improvement. A critical issue in the evolution of SOA is change propagation: given a set of primary changes that have been made to the SOA model, what additional secondary changes are needed to maintain consistency across multiple levels of the SOA models. This paper presents how an existing framework can be applied to effectively support change propagation within a SOA model. We also propose to extend this framework with a minimal modification strategy that helps select change options in a manner that accommodates the structural and semantic dimensions of SOA models.