Yong Zeng

• Ph.D.
• Professor (Full) at Concordia University

Unstructured grid data are essential for modelling complex geometries and dynamics in computational physics. Yet, their inherent irregularity presents significant challenges for conventional machine learning (ML) techniques. This paper provides a comprehensive review of advanced ML methodologies designed to handle unstructured grid data in high-dim...

The utilization of creative design methodologies plays a pivotal role in nurturing innovation within the contemporary competitive market landscape. Although Theory of Inventive Problem Solving (TRIZ) has been recognized as a potent methodology for engendering innovative concepts, its intricate nature and time-consuming learning and application proc...

This study proposed an Environment-Based Design (EBDEA) to develop a draft of information literacy assessment criteria (ILAC), to improve the efficiency of developing ILAC. The approach is validated using two methods. Firstly, a case study is conducted to create ILAC for K-12 students by the EBDEA, resulting in four first-tier and 21 s-tier criteri...

Objectives Adverse event detection from Electronic Medical Records (EMRs) is challenging due to the low incidence of the event, variability in clinical documentation, and the complexity of data formats. Pulmonary embolism as an adverse event (PEAE) is particularly difficult to identify using existing approaches. This study aims to develop and evalu...

BACKGROUND Preprocessing serves to standardize clinical documentation and create consistency throughout all clinical notes. An essential aspect of this process is text normalization, which mainly entails recognizing abbreviations and translating them into their full forms. A range of methods, including Natural Language Processing (NLP) and Machine...

Objective This study aims to investigate the relationship between the subjective performance evaluations on pilot trainees' aircraft control abilities and their brainwave dynamics reflected in the results from EEG microstate analysis. Specifically, we seek to identify correlations between distinct microstate patterns and each dimension included in...

The development of a nonparametric and versatile clustering algorithm has been a longstanding challenge in unsupervised learning due to the exploratory nature of the clustering problem. This study presents a novel algorithm, named Gauging- $\delta$ , which can handle diverse cluster shapes and operate in a nonparametric manner. The algorithm employ...

Unstructured grid data are essential for modelling complex geometries and dynamics in computational physics. Yet, their inherent irregularity presents significant challenges for conventional machine learning (ML) techniques. This paper provides a comprehensive review of advanced ML methodologies designed to handle unstructured grid data in high-dim...

The advancement of artificial intelligence (AI) has enabled researchers to apply this effective tool to several complex cognitive processes, one of which is creativity. Different applications such as creativity assessment, human-AI co-creation, and team creativity enhancement are examples of AI applications to creativity. Although several studies h...

Background Key Performance Indicators (KPIs) are crucial for guiding employees towards organizational goals and providing stakeholders with insights into goal achievement. Developing effective KPIs is particularly challenging for startups due to dynamic environments and limited resources, often requiring extensive domain expertise. Methods This st...

The objective of pilot training is to equip trainees with the knowledge, judgment, and skills to maintain control of an aircraft and respond to critical flight tasks. The present research aims to investigate changes in trainees’ cognitive control levels during a pilot training process while they underwent basic flight maneuvers. EEG microstate anal...

This systematic literature review comprehensively assesses the measurement and quantification of decisional stress using a model-based, theory-driven approach. It adopts a dual-mechanism model capturing both System 1 and System 2 thinking. Mental stress, influenced by factors such as workload, affect, skills, and knowledge, correlates with mental e...

Objective Effective management of hypertension requires not only medical intervention but also significant patient self-management. The challenge, however, lies in the diversity of patients' personal barriers to managing their condition. The objective of this research is to identify and categorize personalized barriers to hypertension self-manageme...

Brain dynamics associated with design creativity tasks are largely unexplored. Despite significant strides, there is a limited understanding of the brain-behavior during design creation tasks. The objective of this paper is to review the concepts of creativity and design creativity as well as their differences, and to explore the brain dynamics ass...

Parkinson's disease (PD) is a debilitating neurodegenerative disease that has severe impacts on an individual's quality of life. Compared with structural and functional MRI-based biomarkers for the disease, electroencephalography (EEG) can provide more accessible alternatives for clinical insights. While deep learning (DL) techniques have provided...

Academic stress has been identified as one of the major issues in education. Prolonged exposure to academic stress can result in serious health and mental issues as well as educational problems. This suggests that academic stress detection is of great importance. Stress has several markers among which physiological markers have been reported to be...

In response to evolving societal and technical demands, this research explores the dynamic landscape of product evolution, focusing on the case study of braking systems. Acknowledging the critical role of product evolution analysis in design phases, the study introduces the Environment-Based Design (EBD) methodology. EBD emphasizes environmental an...

Understanding neural mechanisms in design and creativity processes remains a challenging endeavor. To address this gap, we present two electroencephalography (EEG) datasets recorded in design and creativity experiments. We have discussed the details, similarities, differences, and corresponding cognitive tasks of the two datasets in the following s...

This Extended Editorial has been compiled by the members of the Editorial Board to celebrate the 25th anniversary of the establishment of the Journal of Integrated Design and Process Science, which operates as the Transactions of the Society for Process and Design Science. The paper divides in three parts. The first part provides a detailed overvie...

Waste management systems have always been considered complex. Scholars have studied waste management mostly from a macro perspective for a long time, considering waste management policies as a fraction of this complex system. This study presents the causal variables and feedback relationships related to waste management from another perspective, fr...

When given a 'good' workload, human participants can efficiently complete the assigned task within the time limit, while they may fail to complete it due to low efficiency when given a 'bad' workload. The objective of this research is to investigate how much workload is considered 'good' for individuals to meet a deadline and successfully complete...

A direct sampling method is proposed to generate balanced high-quality training data for mesh generation. • Significantly reducing the learning time of an automatic mesh generator. • Full quadrilateral mesh is generated without human intervention and extra cleanup operations. • The meshing performance is competitive with representative commercial s...

Design is a highly nonlinear chaotic dynamic process with many possible solutions, which requires enormous knowledge for designers. This paper investigates how environment-based design (EBD) methodology can help designers use only necessary knowledge for their creativity based on three methods: information search, knowledge acquisition and knowledg...

Background: In recent years, mHealth has increasingly been used to deliver behavioral interventions for disease prevention and self-management. Computing power in mHealth tools can provide unique functions beyond conventional interventions in provisioning personalized behavior change recommendations and delivering them in real time, supported by d...

Since its inception, research on design methods has encompassed a number of objectives and fields. In this fragmentary and evolving landscape, a reflection was apparently needed on the chance to provide a general framework and understand the progress (if any) towards a unified and domain-independent design theory and methodology. The issue was disc...

Design is a highly nonlinear chaotic dynamic process with many possible solutions, some of which can be creative. The chaotic nonlinearity of design dynamics triggers mental stresses in designers, whose creativity happens only when their mental stresses are at an optimal level. Following a deductive approach, this paper investigates how knowledge c...

Nowadays, bio-inspiration has enhanced the creation of sustainable and innovative solutions to modern engineering problems. Nature could inspire mechanical engineers to develop innovative ideas as a great source for multifunctional and optimized designs. However, it is very difficult to extract desired design knowledge from primarily text-based dat...

Project-based design method is widely used in engineering design education. However, it is time-consuming to develop design thinking skills through projects. This paper proposes that learning methodology and projects will significantly improve students' learning experience and outcomes. The TASKS framework is used to analyze the pros and cons of th...

Project-based design method is widely used in engineering design education. However, it is time-consuming to develop design thinking skills through projects. This paper proposes that learning methodology and projects will significantly improve students’ learning experience and outcomes. The TASKS framework is used to analyze the pros and cons of th...

This paper proposes, implements, and evaluates a reinforcement learning (RL)-based computational framework for automatic mesh generation. Mesh generation plays a fundamental role in numerical simulations in the area of computer aided design and engineering (CAD/E). It is identified as one of the critical issues in the NASA CFD Vision 2030 Study. Ex...

This paper proposes a novel framework for building semantic networks from a seed design statement using Recursive Object Modeling (ROM), Word2Vec language modelling, and vector semantic-based method. Semantic Scholar API was used to retrieve abstracts of scientific papers to build ROM-based Semantic Networks to address the design problem implied in...

A growing trend in requirements elicitation is the use of machine learning (ML) techniques to automate the cumbersome requirement handling process. This literature review summarizes and analyzes studies that incorporate ML and natural language processing (NLP) into demand elicitation. We answer the following research questions: (1) What requirement...

Existing data quality criteria often focus on the quality of the data itself while overlooking other aspects such as the relevance between data and downstream tasks. Furthermore, prior to data collection, policy-makers lack ground truths or labelled data, and are unable to filter data using quantitative criteria. To ensure the collection of reliabl...

When given a "good" workload, human beings can efficiently accomplish the assigned task within the time limit, whereas they could fail to complete it due to low efficiency when given a "bad" workload. The objective of the present research is thus to investigate how much workload is a "good" workload for a human being to meet the deadline with a suc...

Qualitative data analysis is produced frequently in healthcare settings, which is a time-consuming and skilled analytic task. The use of qualitative research findings in clinical settings takes years, which is sometimes obsolete knowledge as the health context is dynamic. Artificial Intelligence (AI)-based qualitative data analysis might present wi...

This paper aims to improve students’ learning performance by optimizing their mental stresses in learning through proposing a new course timetabling method. This new method is based on two hypotheses that formulate the link between course timetabling and learning experience: i) a student’s learning performance is superior when the student is subjec...

Background Measurement of care quality and safety mainly relies on abstracted administrative data. However, it is well studied that administrative data-based adverse event (AE) detection methods are suboptimal due to lack of clinical information. Electronic medical records (EMR) have been widely implemented and contain detailed and comprehensive in...

With the emergence of information systems, computer technologies to understand users have become essential. Applying and developing user-centered design methodology was a reply to this new trend. The main characteristic of HCD/UCD is the involvement of humans (users) in the design process. HCD/UCD accommodates human engagement from the beginning of...

Purpose The purpose of this paper is to analyze theory of inventive problem-solving (TRIZ) in terms of knowledge, skill, workload and affect to understand its effectiveness in enabling designers to achieve their optimized mental performance. Design/methodology/approach TASKS framework, which aims to capture the causal relations among Task workload...

Although emotional or affective working memory (WM) is quite well established in general psychology, not much research has looked into its potential implications for the language sciences and bilingualism and second language acquisition (SLA) research until recently. To fill this gap, this paper aims to propose that WM has not just cognitive implic...

BACKGROUND In recent years, mHealth has increasingly been used to deliver behavioral interventions for disease prevention and self-management. Computing power in mHealth tools can provide unique functions beyond conventional interventions in provisioning personalized behavior change recommendations and delivering them in real time, supported by dia...

There are several challenges in diabetes care management including optimizing the currently used therapies, educating patients on selfmanagement, and improving patient lifestyle and systematic healthcare barriers. The purpose of performing a systems approach to implementation science aided by artificial intelligence techniques in diabetes care is t...

This paper proposes, implements, and evaluates a Reinforcement Learning (RL) based computational framework for automatic mesh generation. Mesh generation, as one of six basic research directions identified in NASA Vision 2030, is an important area in computational geometry and plays a fundamental role in numerical simulations in the area of finite...

Background:: Every human action begins with decision-making. Stress is a significant source of biases that can influence human decision-making. In order to understand the relationship between stress and decision-making, stress quantification is fundamental. Different methods of measuring and quantifying stress in decision-making have been described...

Mind mapping is a visualization tool used in instruction that can be applied by learners to generate ideas, take notes, organize thinking, and develop concepts. Instruction using mind mapping is becoming increasingly commonly used in education. However, research has produced inconsistent results regarding the effectiveness of mind mapping-based ins...

Design is a ubiquitous, complex, and open-ended creation behaviour that triggers creativity. The brain dynamics underlying design is unclear, since a design process consists of many basic cognitive behaviours, such as problem understanding, idea generation, idea analysis, idea evaluation, and idea evolution. In this present study, we simulated the...

The research question is to identify personalized patients' barriers in hypertension self-management, such as physical activities, healthy diet, regular checkups. Self-management depends on individual capabilities to manage their health conditions, with or without the support of health care providers. Our team is applying the TASKS framework to det...

As sustainability becomes increasingly important, product design is taking a proactive role in producing products that are both useful and sustainable. This paper introduces and discusses a tool named Environment-based life cycle decomposition (eLCD) to adapt the Environment-based Design (EBD) methodology to sustainable design. The eLCD brings to E...

As the urban population grows and the global economy develops, municipal solid waste management (MSWM) has become an increasingly prominent global issue. MSWM is particularly difficult in developing countries due to its high cost and time-consuming nature. The Environment-based design (EBD) can potentially contribute to global MSWM by reducing cost...

Implementation is ubiquitous. The identification of barriers to implementation is critical for achieving implementation success. This paper introduces and discusses a deductive theory-based framework, TASKS, to guide the identification of implementation barriers. The TASKS framework deals with the relationships between a Task and the task implement...

Biomass is an abundant energy source, particularly in Canada, as an alternative or primary source for electricity generation. However, low economy of scale could cause a loss of efficiency for bioenergy adoption in small remote communities. In this sense, coordination among the players could promote the efficiency and profitability of bioenergy sup...

Automatic generation of high-quality meshes is a base of CAD/CAE systems. The element extraction is a major mesh generation method for its capabilities to generate high-quality meshes around the domain boundary and to control local mesh densities. However, its widespread applications have been inhibited by the difficulties in generating satisfactor...

Many neurocognitive studies endeavor to understand neural mechanisms of basic creative activities in strictly controlled experiments. However, little evidence is available regarding the neural mechanisms of interactions between basic activities underlying creativity in such experiments. Moreover, strictly controlled experiments might limit flexibil...

This paper proposes a task-related electroencephalogram research framework (tEEG framework) to guide scholars' research on EEG-based cognitive and affective studies in the context of design. The proposed tEEG framework aims to investigate design activities with loosely controlled experiments and decompose a complex design process into multiple prim...

This paper aims to addresses three questions related to conceptual design: 1) Why is environment important? 2) What is environment? and 3) How to analyze environment? Unlike product-, function (affordance)-, or user-centered methodologies, it is argued that the known environment of a product to be designed must be the first thing to be looked at in...

Information collection may affect the design quality and designer's performance through changing the structure of information and the way how information is searched and organized. Based on the theoretical analysis conducted by Wang et al., the present work continues to investigate the influence of designer's natural choice of information collectio...

Project-based learning is an inevitable part of current course curriculums, especially in engineering design courses. Incorporating course projects in curriculums is done for overcoming the lack of students’ familiarity with real-world challenges. Students either acquire or further develop those specific competencies upon successful completion of t...

Recently, physiological signals such as eye-tracking and gesture analysis, galvanic skin response (GSR), electrocardiograms (ECG), and electroencephalograms (EEG) have been used by design researchers to extract significant information to describe the conceptual design process. We study a set of video-based design protocols recorded on subjects perf...

Design protocol data analysis methods form a well-known set of techniques used by design researchers to further understand the conceptual design process. Verbal protocols are a popular technique used to analyze design activities. However, verbal protocols are known to have some limitations. A recurring problem in design protocol analysis is to segm...

A deep learning approach is focused on understanding concepts, analyzing ideas, and creating a strong connection between them and prior knowledge to solve real problems. A capstone project, considered as deep learning approach, is a widely-adopted educational strategy designed to teach students to use their engineering knowledge to solve real-life...

– The effectiveness of aerospace design engineering education has received a great deal of anecdotal feedback from its stakeholders. The aerospace industry, the Canadian government, the University, and the enrolled engineering students have expressed customer needs and expectations of design engineering training. While numerous curriculum reform in...

– Engineering design is a decision making process that needs a good perception of the design problem to be solved. Design problems are usually solved in a team. Teams need the existence of a good design problem perception to create design solutions. This study provides an approach for elaborating a descriptive model to describe how the perception p...

– Considering the challenges in the aerospace industry, the NSERC (Natural Sciences and Engineering Research Council of Canada) Chair in Aerospace Design Engineering (NCADE) has launched its own version of a final year undergraduate engineering capstone project at Concordia University. NCADE’s objective is to expose students to the immense complexi...

A wide variety of research topics on emotional engineering has demonstrated that emotional engineering has attracted a lot of attention recently, and more researchers have realized the importance of emotion in engineering. Some of the efforts are focused on the application of emotion to different phases within a product lifecycle, namely conceive s...

This technical report presents an overview of quantitative EEG methods commonly used to detect cognitive and affective states. The paper covers basic knowledge of EEG recording, preprocessing and analysis methods.

Organizational capability is of particular importance to organizational performance. Existing research in the literature identified a wide range of factors that would contribute to organizational capability. This paper aims to establish a theoretical model that addresses the fundamental elements contributed to organizational capability. We develop...

This paper investigates the relationships between subjective rating measure and physiological measure of mental stress and mental effort during design activities. Mental stress and mental effort were captured by skin conductance and EEG beta2 power (20–30 Hz) whereas self-rated mental stress and self-rated mental effort were obtained using the NASA...

When seeking candidates for engineering design positions, aerospace companies usually seek to hire high qualified professionals while overlooking recent graduates from engineering schools. The reason for this is the opinion that most of the engineers graduating from universities do not possess the skill sets the companies are seeking and that it ta...

Course scheduling is a challenging operations research problem that involves students, faculty members, availability of classrooms, class sizes and many other factors. As it is the case for most scheduling problems, course scheduling is an NP-Hard problem. Due to its challenging nature, frequently the main objective is only to find a feasible solut...

Course scheduling is a challenging operations research problem that involves students, faculty members, availability of classrooms, class sizes and many other factors. As it is the case for most scheduling problems, course scheduling is an NP-Hard problem. Due to its challenging nature, frequently the main objective is only to find a feasible solut...

Electroencephalography (EEG) study of design activities has been drawing increasing attentions in design cognition research. The aim of this present paper is to identify EEG bands that are associated with design activities through principal component analysis (PCA). Based on the analysis of the data on 32 subjects collected from experiments conduct...

Physiological signals are at the core of affective and cognitive engineering methods which aim at providing a more humancentric perspective to engineering concepts and systems. Labelling physiological signals with meaningful words such as concentration, fatigue or effort is a hard task. Although those labels are well-documented in the medical and r...

This paper proposes an approach to generating System Modeling Language (SysML) diagrams from a Recursive Object Model (ROM) diagram. The ROM diagram represents entities (or concepts) and three kinds of relations between these entities found in a description text. The generated SysML models include block definition diagram, use case diagram, and act...

Design fixation describes a phenomenon in which designers fail to solve a design problem due to their strong mental attachment to an internal or external inspiring source. A number of empirical research studies aimed at identifying the causes behind design fixation and developing approaches for overcoming it. In this paper, we propose a theoretical...

Analytic Hierarchy Process (AHP) is a decision making method which has advantages for both qualitative and quantitative analysis. In an engineering field, AHP is often applied, together with other analysis methods, to evaluate the effectiveness of engineering projects. Environment-Based Design (EBD) is a systematic approach to finding creative desi...

This paper presents matching algorithms for two-sided dynamic service markets where service providers and customers form two disjoint sets and an agent from one side of the market can be matched only with an agent from the other side. We address the challenges derived from dynamic changes of the market. The algorithms are designed based on re-match...

As many as one in three first-year undergraduate students cannot make it back for the sophomore year. The low retention rate for students, especially engineering students, is a widespread problem. In this paper, the quantification of course difficulty and student stress is discussed, followed by a student stress model which can integrate student st...

Direct interfacing of computers with the human brain is one of the holy grails of computer science and has been in the computing folklore since the very beginning of computing history. The challenges researchers are facing are non-trivial and the breakthroughs are non-negligeable. Measuring the hardness of a mental task is a fundamental problem in...

This paper summarizes a design methodology - Environment Based Design (EBD) - developed over the last two decades. The EBD stems from the observation that design aims to change an existing environment to a desired one by generating a new artefact. Design starts from the environment, functions for the environment, and brings changes to the environme...