Process-centric Approach Research Articles

Engaging Students to Learn Coding in the AI Era with Emphasis on the Process

Engaging Students to Learn Coding in the AI Era with Emphasis on the Process

Navigating change: an exploration of socio-epistemic process of extending Wikidata ontology with new properties

PurposeThe paper addresses the issue of change in Wikidata ontology by exposing the role of the socio-epistemic processes that take place inside the infrastructure. The subject of the study was the process of extending the Wikidata ontology with a new property as an example of the interplay between the social and technical components of the Wikidata infrastructure.Design/methodology/approachIn this study, an interpretative approach to the evolution of the Wikidata ontology was used. The interpretation framework was a process-centric approach to changes in the Wikidata ontology. The extension of the Wikidata ontology with a new property was considered a socio-epistemic process where multiple agents interact for epistemic purposes. The decomposition of this process into three stages (initiation, knowledge work and closure) allowed us to reveal the role of the institutional structure of Wikidata in the evolution of its ontology.FindingsThis study has shown that the modification of the Wikidata ontology is an institutionalized process where community-accepted regulations and practices must be applied. These regulations come from the institutional structure of the Wikidata community, which sets the normative patterns for both the process and social roles and responsibilities of the involved agents.Originality/valueThe results of this study enhance our understanding of the evolution of the collaboratively developed Wikidata ontology by exposing the role of socio-epistemic processes, division of labor and normative patterns.

Applying a process-centric approach to the digitalization of operations in manufacturing companies: a case study

This research aims to explore how digital technology can enhance productivity in manufacturing firms through the application of lean methodology and Industry 4.0. While previous studies have been primarily theoretical, digital technologies have the potential to improve efficiency in lean organizations. The research develops a practical and effective digitalization framework for manufacturing firms to improve operational efficiency. The proposed framework recommends a step-by-step approach to implementing digital technologies and fostering a culture of digital innovation. The framework will be tested in a real-world manufacturing setting to provide industry practitioners with empirical evidence to support and guide its implementation. The study first focuses on the literature review of Lean Manufacturing, Industry 4.0, and their connection. The methodology adopted for the research is then discussed, followed by the case study. The study concludes that a culture of digital innovation is critical for digitalization success. The study recommends that companies adopt the proposed framework to increase operational efficiency, reduce waste, and gain a competitive advantage. This study provides a practical framework for manufacturing firms to implement digital technologies and improve operational efficiency. The proposed framework is designed to be adaptable and can be customized to meet specific organizational needs. The study highlights the importance of a digital innovation culture and recommends a step-by-step approach to implementing digital technologies in manufacturing firms.

Humán kockázatok hálózatkutatási szempontból

AbstractAim: Networks can be interpreted in the context of corporate processes, which are implemented through “machines” and human resources. Human capital plays a fundamental role in the economy. The human factor appears at all levels of an organization. Human resources form part of process steps and control activities. It is a significant question how to ensure the safe organizational operation from human resources’ perspective in the constantly changing business environment, resp. in case of unforeseen events (e.g., pandemic). The aim of the research is to demonstrate that corporate processes can be interpreted from a network research aspect, to explore the role of networks in corporate processes, to describe the risks associated with the human factor in corporate processes, and to understand the relationships between corporate risks and controls.Methodology: The publication examines the role of the human factor in safety using network research tools in the context of the company’s internal control system. The publication analyses the control network of the revenue process in case study form and explores the controls assigned to the process, the associated human factor, and human risks.Findings: Through the network of controls built into corporate processes, the company can achieve a level of security that meets its risk tolerance, which security is a value that is essential for long-term success. The safety net of systems will be strong enough if it addresses simultaneously the risks of the human factor. It is necessary that the corporate security culture, the values represented by top management to employees and the control-conscious approach can strengthen the control environment and corporate integrity.Value: Adapting to today’s agile business environment calls to move towards a network organizational structure, and to rearrange corporate processes in a process-centric manner. Through the process-centric approach and - management of enterprise processes, process chains are created that can be interpreted as network of processes. Control activities shall be assigned to the processes, their successful implementation will help to achieve the desired level of security. Secure organizational operations mean value. The human factor involved in the processes will always be present in varying proportions; therefore, it is necessary to identify and manage the risks associated with the human factor.

Modernizing Legacy Software as Context—Sensitive and Portable Mobile-Enabled Application

Mobile systems support portable, context-sensitive, and interactive computing that empower users to perform complex computations and communications on the go. Majority of the existing software systems run on web or workstation-based (traditional computing) platforms, lacking the capabilities of mobile systems, and are referred to as legacy software. The primary contribution of this research is a process-centric approach that enables automation and user decision support to modernize legacy software as context-sensitive and portable mobile-enabled application. Case study based validation complements the modernization process with scenario-based demonstration of the solution and qualitative evaluation of the modernized application. Evaluation results suggest that modernized application supports portable and context-sensitive computations, efficient utilization of device resources, and ease of use.

Refocusing the climate services lens: Introducing a framework for co-designing “transdisciplinary knowledge integration processes” to build climate resilience

This paper seeks to reconceptualize climate services in light of the prevailing inability of existing climate information to spur needed policy and action. We propose refocusing the climate services lens by moving away from a narrow, supply-driven emphasis on products. Instead, we advocate moving towards a process-centric approach defined by transdisciplinary collaboration that purposefully seeks to bring about fundamental, long-term benefits. Such benefits include increased human and institutional capacity, and the creation of relationships that are essential components of science-informed decision-making for climate adaptation and beyond. Work underpinning this paper consists of a review of existing climate services guidance, and analyses of a survey of climate services stakeholders, and a climate information co-production process case study in Lusaka, Zambia. We identify elements needed to support complex, real-world decision-making that many existing climate services fail to sufficiently consider. We respond by introducing a framework (Tandem), which consists of structured elements and practical, guiding questions informed by empirical analysis. To lay the foundation for both science-informed policy and policy-informed science, the Tandem framework puts forward guidance to achieve three goals: 1) to improve the ways in which all participants work together to purposefully design transdisciplinary knowledge integration processes (co-exploration and co-production processes that bring together different knowledge types across the science-society interface); 2) to co-explore decision-relevant needs for the co-production of integrated climate information (i.e., decision-relevant climate and non-climate information); and, 3) to increase individual and institutional capacities, collaboration, communication and networks that can translate this information into climate-resilient decision-making and action.

Bioengineering for multiple PAHs degradation for contaminated sediments: Response surface methodology (RSM) and artificial neural network (ANN)

Scientific community around the globe have major focus on designing bioremediation strategies for persistent, recalcitrant, highly toxic and carcinogen/mutagen polycyclic aromatic hydrocarbons (PAHs) present in marine environment. For the bioremediation strategy, components of growth medium are a key factor, which enhance degradation of the PAHs through simulating the microbial growth. Thus, present study involves bioengineering of growth medium (ONR7a) using response surface methodology (RSM) and artificial neural network (ANN) for enhanced multiple PAHs biodegradation. Microbes were isolated from contaminated sediments of Alang Sosiya Ship Breaking Yard (ASSBRY), Gulf of Khambhat, Gujarat, India. RSM - a process centric approach has resulted in an increase in PAHs degradation from 69% (Unoptimized) to 90.03% with 1.29 folds increase on 5th day with R2 value of 0.98. Moreover, use of Artificial Neural Network (ANN) – a data centric approach resulted in better prediction of PAHs degradation of 93.36% compared to the CCD-RSM predicted PAHs degradation of 90.03% with R2 value of 0.98. Based on various error functions such as mean absolute deviation (MAD), mean squared error (MSE), root mean squared error (RMSE) and mean absolute percentage error (MAPE), the predictive ability of the constructed ANN models was found to be higher compared to RSM. As this is the first ever report on PAHs degradation by bacterial mixed culture using data centric approach, this study bridges the gap between fundamental research and its application for policymakers and stakeholders which would be helpful in designing appropriate bioremediation technologies.

Thinking and Thinking About Thinking: A Qualitative Study of Learning in a Process-Centric Teaching Model

ABSTRACTIn the 21st-century sociotechnical context where humans are steeped in information, approaches to social work education that foster students’ capacities to critically consume and be well poised to reflexively apply information are critical. This article presents findings from a qualitative study designed to deepen understanding of social work students’ thinking, thinking about thinking, and changes that emerged through a process-centric approach to human behavior in the social environment. Data were gathered from 52 students and analyzed thematically using a constructionist-informed grounded theory framework. An overarching theme of deepening empathic awareness emerged, with three nested subthemes, capturing shifts in thinking. This article offers a conceptual framework that emerged from the data that can inform the development of process-centric approaches to social work education and future research.

Extending Data Quality Management for Smart Connected Product Operations

Smart connected product (SCP) operation embodies the concept of the internet of things (IoT). To increase the probability of success of SCP operations for customers, the high quality of the IoT data across operations is imperative. IoT data go beyond sensor data, as integrate some other various type of data such as timestamps, device metadata, business data, and external data through SCP operation processes. Therefore, traditional data-centric approaches that analyze sensor data and correct their errors are not enough to preserve, in long-term basis, adequate levels of quality of IoT data. This research provides and alternative framework of data quality management as a process-centric approach to improve the quality of IoT data. The proposed framework extends the process reference model (PRM) for data quality management (DQM) defined in ISO 8000-61, and tailored to fully adapt to the special requirements of the IoT data management. These involve several adaptations: first, the scope of the SCP operations for data quality management is determined, and the processes required for SCP operations are defined following the process description format of ISO 8000-61. Second, the relationship between the processes and the structure of the processes in the technology stack of the SCP operations are described to cover the actual nature of the IoT data flows. Finally, a new IoT DQM-PRM is proposed by integrating the processes for the SCP operations with DQM-PRM. When these processes are executed in the organization, the quality of IoT data composed of data of various types can be continuously improved and the utilization rate of SCP operations is expected to increase.

Designing Effective Visual Interactive Systems despite Sparse Availability of Domain Information

Tailoring visualization and interaction design to the demands of an application is challenging if domain information is unavailable or confidential. This article discusses a process-centric design approach, allowing for inferring design goals indirectly from informal interviews with practitioners and stakeholders. The design benefits from their expertise, while secrets remain secret.

Personality Process-Structure Duality: Reply to Two Commentaries.

In two commentaries, Kostromina and Grishina (2018) and Mironenko (2018) offered constructive thoughts and questions in response to an article by Giordano (2018, Culture & Psychology, 23, 502-518) on the merits of an approach to understanding individual personality that focuses on the processes rather than structures of personality. In this reply, the authors seek to clarify some of the points made in the original article. The authors also describe a personality process-structure duality, whereby personality is conceptualized in terms of processes or structures based on the methods used to study it. If the goal is to understand the dynamic and emergent properties of individual personality, the authors continue to argue for the merits of a process-centric approach and the avoidance of structural thinking.

A Big-Data based and process-oriented decision support system for traffic management

Data analysis and monitoring of road networks in terms of reliability and performance are valuable but hard to achieve, especially when the analytical information has to be available to decision makers on time. The gathering and analysis of the observable facts can be used to infer knowledge about traffic congestion over time and gain insights into the roads safety. However, the continuous monitoring of live traffic information produces a vast amount of data that makes it difficult for business intelligence (BI) tools to generate metrics and key performance indicators (KPI) in nearly real-time. In order to overcome these limitations, we propose the application of a big-data based and process-centric approach that integrates with operational traffic information systems to give insights into the road network's efficiency. This paper demonstrates how the adoption of an existent process-oriented DSS solution with big-data support can be leveraged to monitor and analyse live traffic data on an acceptable response time basis.

Bioengineering for multiple PAHs degradation using process centric and data centric approaches

The study aims sequential bioengineering for multiple PAHs degradation using a process centric approach – response surface methodology (RSM) and a data centric approach – artificial neural networks (ANN). The study involves stepwise media optimization protocol for multiple PAHs degradation using newly isolated Stenotrophomonas maltophilia. RSM, a non linear model has predicted 94.70% degradation on 5th day with R2 value of 0.97. The analysis of desirability revealed the optimum value of the process conditions: NaCl – 27.55 g/L; NH4Cl- 0.28 g/L; Na2HPO4- 0.08 g/L, TAPSO- 1.74 g/L. Feed forward ANN, a linear model has predicted 95.94% degradation with R2 value of 0.99. The change in the magnitude of error functions viz. root mean square error (RMSE), mean absolute deviation (MAD) and mean absolute percentage error (MAPE) were low during ANN prediction as compared to RSM. Moreover, sensitivity analysis of both models also proves efficiency of the prediction capability and generalization of the data. Thus, for the very first time chemometrics study of medium components for multiple PAHs degradation offers constructive and powerful alternative to scientific community to design microcosm and mesocosm experiments.

Application of FMEA to Study the Risk Perception of SMEs Throughout the ERP Adoption Life Cycle

In this paper, the authors have tried to validate the risk perception of ERP adoption in SMEs using Failure Modes and Effects Analysis (FMEA). The work significantly contributes to the existing body of ERP adoption knowledge to the SMEs. Foremost, an ERP adoption life cycle addressed to SMES comprising of five distinct phases is proposed. Second, a well-laid out inventory of risk factors have been identified. Third, FMEA is applied to understand, validate the risk perception of respondents on ERP adoption in SMEs. Exploiting the ERP System, Inadequate financial management, Lack of Owners' Commitment, Ineffective communication with users and change in project scope are the top five highest perceived risks based on the risk perception number (RPN). The process centric approach to system implementation through FMEA also prescribes pertinent recommendations to the stakeholder ecosystem to proactively defend against vulnerabilities during the ERP adoption life cycle.

Individual personality is best understood as process, not structure: A Confucian-inspired perspective

A structural approach to understanding personality, which is rooted in a being or substance ontology, is most useful for making between individual and group comparisons. In contrast, a process-centric approach, which is anchored in a Becoming or event-based ontology, is most helpful for understanding individual personality process and variation. A process-centric model, using classical Confucianism as a starting point, has a number of advantages in that it (1) integrates persons and situations, (2) is inherently relational, which implies an aesthetic dimension to personality development and functioning, (3) focuses on the uniqueness of individual personalities, (4) views qualitative and quantitative inquiry as complementary and of equal scientific value, and (5) encourages intra- and inter-disciplinary collaborations.

Towards a new process-centric approach of social mediation management in Morocco

Towards a new process-centric approach of social mediation management in Morocco

Bioengineering for polycyclic aromatic hydrocarbon degradation by Mycobacterium litorale: Statistical and artificial neural network (ANN) approach

The study deals with the modeling for enhancing fluoranthene biodegradation using a conventional process-centric approach response surface methodology, and a comparatively newer, data-centric approach artificial neural network. The study deals with the comparison of two models for enhancing fluoranthene biodegradation using Mycobacterium litorale. The study involves step wise optimization protocol incorporating screening of medium components. The variables of interest were CaCl2, KH2PO4 and, NH4NO3, screened based on Plackett-Burman model. The second step involves the CCD matrix, resulting in 51.21% degradation on the 3rd day with R2 value 0.9882. The non-linear multivariate ANN has model predicted 51.28% degradation with 0.9987 R2 value. The root mean square error and mean absolute percentage error values were found to be 0.3234 and 0.5715, respectively. The entire approach has resulted in 51.28% degradation on 3rd day as compared to an unoptimized degradation (26.37%) on 7th day. The values obtained by ANN network were more precise, reliable and reproducible, compared to the conventional RSM model, proving the superiority of ANN model over RSM model. The study thus widens the current understanding of the scientific community for the fabrication, forecasting precisely simulated biological process for green technology.

Being or Becoming: Toward an Open-System, Process-Centric Model of Personality

Mainstream personality psychology in the West neglects the investigation of intra-individual process and variation, because it favors a Being over a Becoming ontology. A Being ontology privileges a structural (e.g., traits or selves) conception of personality. Structure-centric models in turn suggest nomothetic research strategies and the investigation of individual and group differences. This article argues for an open-system, process-centric understanding of personality anchored in an ontology of Becoming. A classical Confucian model of personality is offered as an example of a process-centric approach for investigating and appreciating within-person personality process and variation. Both quantitative and qualitative idiographic strategies can be used as methods of scientific inquiry, particularly the exploration of the Confucian exemplar of psychological health and well-being.

Automatic Verification of Database-Centric Systems

Automatic Verification of Database-Centric Systems Alin Deutsch Richard Hull Victor Vianu UC San Diego IBM Yorktown Research Center UC San Diego & INRIA Saclay deutsch@cs.ucsd.edu vianu@cs.ucsd.edu hull@us.ibm.com INTRODUCTION area of business process management, concomitantly with an evolution from the traditional process-centric approach towards data awareness. A notable expo- nent of this class is the business artifact model pio- neered in [63, 51], deployed by IBM in professional services. Business artifacts (or simply “artifacts”) model key business-relevant entities, which are up- dated by a set of services that implement business process tasks. A collection of artifacts and services is called an artifact system. This modeling approach has been successfully deployed in practice [7, 6, 21, 27, 69], and has been adopted in the OMG standard for Case Management [9]. Tools such as the above automatically generate the database-centric application code from the high- level specification. This not only allows fast proto- typing and improves programmer productivity but, as a side effect, provides new opportunities for au- tomatic verification. Indeed, the high-level specifi- cation is a natural target for verification, as it ad- dresses the most likely source of errors (the applica- tion’s specification, as opposed to the less likely er- rors in the automatic generator’s implementation). The theoretical and practical results obtained so far concerning the verification of such systems are quite encouraging. They suggest that, unlike arbi- trary software systems, significant classes of data- driven systems may be amenable to automatic veri- fication. This relies on a novel marriage of database and model checking techniques, and is relevant to both the database and the computer-aided verifica- tion communities. In this article, we describe several models and re- sults on automatic verification of database-driven systems, focusing on temporal properties of their underlying workflows. To streamline the presenta- tion, we focus on verification of business artifacts, and use it as a vehicle to introduce the main con- cepts and results. We then summarize some of the work pertaining to other applications such as data- driven web services. Software systems centered around a database are pervasive in numerous applications. They are en- countered in areas as diverse as electronic commerce, e-government, scientific applications, enterprise in- formation systems, and business process manage- ment. Such systems are often very complex and prone to costly bugs, whence the need for verifica- tion of critical properties. Classical software verification techniques that can be applied to such systems include model check- ing and theorem proving. However, both have se- rious limitations. Indeed, model checking usually requires performing finite-state abstraction on the data, resulting in loss of semantics for both the sys- tem and properties being verified. Theorem proving is incomplete, requiring expert user feedback. Recently, an alternative approach to verification of database-centric systems has taken shape, at the confluence of the database and computer-aided ver- ification areas. It aims to identify restricted but sufficiently expressive classes of database-driven ap- plications and properties for which sound and com- plete verification can be performed in a fully auto- matic way. This approach leverages another trend in database-driven applications: the emergence of high-level specification tools for database-centered systems, such as interactive web applications and data-driven business processes. We review next a few representative examples. A commercially successful high-level specification tool for web applications is Web Ratio [1], an out- growth of the earlier academic prototype WebML [20, 17]. Web Ratio allows to specify a Web ap- plication using an interactive variant of the E-R model augmented with a workflow formalism. Non- interactive variants of Web page specifications had already been proposed in Strudel [39], Araneus [58] and Weave [40], targeting the automatic generation of Web sites from an underlying database. High- level specification tools have also emerged in the

Application of the tectono-geochemistry method to mineral prospectivity mapping: a case study of the Gaosong tin-polymetallic deposit, Gejiu district, SW China

The tectono-geochemistry method as a lithogeochemical exploration tool is a process centric approach based on the premise that element migration and concentration within and adjacent to geological structures are controlled by large-scale dynamic earth processes that operate on a variety of scales to focus mass and energy flux. Here we present a case study of the Gaosong tin-polymetallic deposit, Gejiu district, SW China, illustrating how the tectono-geochemistry method can be applied to mineral prospectivity mapping. As a first step, 2216 fault rock samples collected within the Geiju district were assayed followed by a detailed examination of the assay results by means of factor analysis and multifractal singularity mapping. The main aims of these analyses were to (1) statistically explore the data with respect to specific element concentrations, associations and geochemical patterns by which the fault rock samples can be grouped, (2) better characterize the samples in terms of whether or not the rocks recorded any evidence for hydrothermal mineralization processes, and (3) identify any geochemical anomalies that may present vectors to buried ore. The results illustrate that element distribution patterns are greatly influenced by fault permeability and that NE-SW-striking faults are the most favorable in terms of concentration of ore elements. Factor analysis greatly assisted the identification and interpretation of, for example, element associations, and geochemical zonation patterns genetically related to intrusions. Recognition of singularities was of particular importance with respect to identifying and delineating primary fault tectono-geochemical anomalies that may be caused by buried ore. Of particular interest are low singularity values as these correspond with positive geochemical anomalies over known ore deposits in the Gejiu district. Anomalies delineated by local singularity exponents may represent undiscovered ore and, thus, warrant further exploration.