scholarly journals Using Machine Learning in Business Process Re-Engineering

2021 ◽  
Vol 5 (4) ◽  
pp. 61
Author(s):  
Younis Al-Anqoudi ◽  
Abdullah Al-Hamdani ◽  
Mohamed Al-Badawi ◽  
Rachid Hedjam
Keyword(s):  
Machine Learning ◽  
Business Process ◽  
Process Management ◽  
Scientific Publication ◽  
Lean Six Sigma ◽  
British Library ◽  
Machine Learning Model ◽  
Machine Learning Applications ◽  
Implementation Costs ◽  
Tools And Techniques

A business process re-engineering value in improving the business process is undoubted. Nevertheless, it is incredibly complex, time-consuming and costly. This study aims to review available literature in the use of machine learning for business process re-engineering. The review investigates available literature in business process re-engineering frameworks, methodologies, tools, techniques, and machine-learning applications in automating business process re-engineering. The study covers 200+ research papers published between 2015 and 2020 in reputable scientific publication platforms: Scopus, Emerald, Science Direct, IEEE, and British Library. The results indicate that business process re-engineering is a well-established field with scientifically solid frameworks, methodologies, tools, and techniques, which support decision making by generating and analysing relevant data. The study indicates a wealth of data generated, analysed and utilised throughout business process re-engineering projects, thus making it a potential greenfield for innovative machine-learning applications aiming to reduce implementation costs and manage complexity by exploiting the data’s hiding patterns. This suggests that there were attempts towards applying machine learning in business process management and improvement in general. They address process discovery, process behaviour prediction, process improvement, and process optimisation. The review suggests that expanding the applications to business process re-engineering is promising. The study proposed a machine-learning model for automating business process re-engineering, inspired by the Lean Six Sigma principles of eliminating waste and variance in the business process.

scholarly journals An Introduction on Interpretable Machine Learning

2020 ◽  
Vol 9 (7S) ◽  
pp. 107-111
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Human Life ◽  
Accuracy Score ◽  
Learning Models ◽  
Ethical Practices ◽  
Interpretable Machine Learning ◽  
Machine Learning Model ◽  
Machine Learning Applications ◽  
Machine Learning Models

As Artificial Intelligence penetrates all aspects of human life, more and more questions about ethical practices and fair uses arise, which has motivated the research community to look inside and develop methods to interpret these Artificial Intelligence/Machine Learning models. This concept of interpretability can not only help with the ethical questions but also can provide various insights into the working of these machine learning models, which will become crucial in trust-building and understanding how a model makes decisions. Furthermore, in many machine learning applications, the feature of interpretability is the primary value that they offer. However, in practice, many developers select models based on the accuracy score and disregarding the level of interpretability of that model, which can be chaotic as predictions by many high accuracy models are not easily explainable. In this paper, we introduce the concept of Machine Learning Model Interpretability, Interpretable Machine learning, and the methods used for interpretation and explanations.

scholarly journals A Real-time LAN/WAN and Web Attack Prediction Framework Using Hybrid Machine Learning Model

2018 ◽  
Vol 7 (3.12) ◽  
pp. 1128
Author(s):  
Mohammad Arshad ◽  
Md. Ali Hussain
Keyword(s):  
Machine Learning ◽  
Intrusion Detection ◽  
Real Time ◽  
Learning Model ◽  
Attack Detection ◽  
Buffer Size ◽  
Learning Classifier ◽  
Network Intrusion ◽  
Machine Learning Model ◽  
Tools And Techniques

Real-time network attacks have become an increasingly serious issue to LAN/WAN security in recent years. As the size of the network flow increases, it becomes difficult to pre-process and analyze the network packets using the traditional network intrusion detection tools and techniques. Traditional NID tools and techniques require high computational memory and time to process large number of packets in incremental manner due to limited buffer size. Web intrusion detection is also one of the major threat to real-time web applications due to unauthorized user’s request to web server and online databases. In this paper, a hybrid real-time LAN/WAN and Web IDS model is designed and implemented using the machine learning classifier. In this model, different types of attacks are detected and labelled prior to train the machine learning model. Future network packets are predicted using the trained machine learning classifier for attack prediction. Experimental results are simulated on real-time LAN/WAN network and client-server web application for performance analysis. Simulated results show that the proposed machine learning based attack detection model is better than the traditional statistical and rule based learning models in terms of time, detection rate are concerned.  

scholarly journals Computational analysis of tongue image for health diagnosis

2017 ◽  
Author(s):  
◽  
Meng Zhang
Keyword(s):  
Machine Learning ◽  
Image Analysis ◽  
Image Segmentation ◽  
The Body ◽  
Support Vector ◽  
Classification Image ◽  
Machine Learning Model ◽  
Machine Learning Applications ◽  
User Friendly ◽  
Traditional Chinese Medical

Tongue, the primary taste organ in the mouth, can reflect the whole body's health conditions based on the Traditional Chinese Medical (TCM) theories. Watching the tongue is one of the most common, essential and reliable methods for the TCM doctor to make diagnoses. In this thesis, a new health system is introduced based on tongue image analysis. The technologies adopted in this system ranged from tongue image processing algorithms to machine learning applications. The tongue image algorithms used in this work include image segmentation, tongue recognition and tongue image classification. Image segmentation was used to get rid of other unrelated parts, such as lip, face and neck, while keeping the tongue only. Then two recognition methods were applied to check whether the segmented result is a tongue or not. For different tongue patterns, the Support Vector Machine is applied to train a machine learning model and make predictions to classify the tongue into different labeled groups. An app named 'iTongue' is designed to monitor the body status by taking and processing tongue images in smart phones. The app provides a user-friendly, fast and powerful health tool based on TCM theories. The whole system is implemented in a webbased environment. An advanced portal was developed to connect the users and the TCM doctors. The users will not only obtain the analysis label of tongue images, but also get some life style recommendations based on the tongue image analysis. This portal helps the user understand more about his body status and guide him to adopt a more suitable diet and improve exercise.

scholarly journals The Link between Business Process Management and Quality Management

2020 ◽  
Vol 13 (10) ◽  
pp. 225
Author(s):  
Inga Stravinskiene ◽  
Dalius Serafinas
Keyword(s):  
Quality Management ◽  
Business Process ◽  
Business Process Management ◽  
Process Management ◽  
Lean Six Sigma ◽  
Management Systems ◽  
Business Organizations ◽  
Quality Management Systems ◽  
Management Paradigms ◽  
Almost All

In an environment of intense globalization and digitalization, business organizations are increasingly faced with various challenges such as rising costs, strong competition, rapidly evolving technologies, increasingly demanding and whimsical consumers, and, in social terms, changing societal demands. It is within this context that the effectiveness and efficiency of the management of business organizations is actualized. The paper addresses the following fundamental questions regarding the scientific problem at the theoretical level: What is the place of Business Process Management (BPM) in the context of Quality Management (QM)? Should BPM be the axis of QM? There is a lack of interdisciplinary research on the link between Business Process Management and Quality Management, and this study aims to ground this link. Methods of the research are literature review and the critical analysis of the scientific sources on the issue. The findings show that there exists confusion, overlaps among different paradigms of QM and BPM. The BPM paradigm might be considered as an integral part of almost all essential quality management paradigms. BPM is like a horizontal area “crossing” different paradigms of quality management (e.g., TQM, SMS, Lean, Six Sigma). The conclusions drawn are useful for organizations that implement quality management systems. The integration of BPM into quality management systems and tools creates preconditions for the development of an effective and efficient organization.

scholarly journals Business Process Management SaaS para la gestión de proyectos concursables en un contexto universitario

2019 ◽  
Vol 8 (3) ◽  
Author(s):  
Nemias Saboya Rios ◽  
Esteban Tocto-Cano ◽  
Edward J. Aguilar Alvarado ◽  
Omar Loaiza Jara
Keyword(s):  
Business Process ◽  
Six Sigma ◽  
Business Process Management ◽  
Process Management ◽  
Lean Six Sigma

BPM es una metodología que está enfocada principalmente a la gestión de procesos, más que en sus resultados; a comparación de otras como la gestión de la calidad total (TQM), Lean, Six sigma entre otros. El propósito de la investigación fue elaborar un modelo de proceso para mejorar la gestión de proyectos concursables en un contexto universitario con el enfoque Business Process Management SaaS. El tipo de investigación fue de tipo aplicada con enfoque cuantitativo y a su vez tecnológica porque se propuso formalizar el proceso apoyado con una aplicación en la nube bajo el enfoque BPM SaaS. Para el desarrollo de la investigación se utilizó las herramientas de la suite de Bizagi Studio para el diseño de los procesos y para la contratación de los resultados se elaboró un instrumento que fue validado por expertos y aplicado a representantes de docentes, administradores y estudiantes. Los resultados demostraron que el proceso para gestionar los proyectos concursables cumplen de manera efectiva con los requerimientos establecidos, de modo que los resultados estadísticos corroboran que el 60% y el 100% de los que validaron el proceso indicaron que el modelamiento y el diseño están en un nivel Excelente y el 90% de los mismos manifestaron que el monitoreo y la ejecución del proceso se encuentran en el mismo nivel. El estudio realizado demostró que a partir del diseño, modelado, control y ejecución del proceso propuesto basado en BPM SaaS logró que contribuya a la gestión de los proyectos concursables.

scholarly journals Business Process Management SaaS para la gestión de proyectos concursables en un contexto universitario

2018 ◽  
Vol 8 (3) ◽  
pp. 77-95
Author(s):  
Nemias Saboya Rios ◽  
Esteban Tocto Cano ◽  
Edward Jean Pierre Aguilar Alvarado ◽  
Omar Loaiza Jara
Keyword(s):  
Business Process ◽  
Six Sigma ◽  
Business Process Management ◽  
Process Management ◽  
Lean Six Sigma

BPM es una metodología que está enfocada principalmente a la gestión de procesos, más que en sus resultados; a comparación de otras como la gestión de la calidad total (TQM), Lean, Six sigma entre otros. El propósito de la investigación fue elaborar un modelo de proceso para mejorar la gestión de proyectos concursables en un contexto universitario con el enfoque Business Process Management SaaS. El tipo de investigación fue de tipo aplicada con enfoque cuantitativo y a su vez tecnológica porque se propuso formalizar el proceso apoyado con una aplicación en la nube bajo el enfoque BPM SaaS. Para el desarrollo de la investigación se utilizó las herramientas de la suite de Bizagi Studio para el diseño de los procesos y para la contratación de los resultados se elaboró un instrumento que fue validado por expertos y aplicado a representantes de docentes, administradores y estudiantes. Los resultados demostraron que el proceso para gestionar los proyectos concursables cumplen de manera efectiva con los requerimientos establecidos, de modo que los resultados estadísticos corroboran que el 60% y el 100% de los que validaron el proceso indicaron que el modelamiento y el diseño están en un nivel Excelente y el 90% de los mismos manifestaron que el monitoreo y la ejecución del proceso se encuentran en el mismo nivel. El estudio realizado demostró que a partir del diseño, modelado, control y ejecución del proceso propuesto basado en BPM SaaS  logró que contribuya a la gestión de los proyectos concursables.

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