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Hyperparameter optimization for cardiovascular disease data-driven prognostic system

Visual Computing for Industry,Biomedicine,and Art 2023年第1期6卷 218-244页

作者： Jayson Saputra Cindy Lawrencya Jecky Mitra Saini Suharjito Suharjito Industrial Engineering Department BINUS Graduate Program-Master of Industrial EngineeringBina Nusantara UniversityJakarta 11480Indonesia

Prediction and diagnosis of cardiovascular diseases(CVDs)based,among other things,on medical examinations and patient symptoms are the biggest challenges in *** 17.9 million people die from CVDs annually,accounting for 31%of all deaths *** a timely prognosis and thorough consideration of the patient’s medical history and lifestyle,it is possible to predict CVDs and take preventive measures to eliminate or control this life-threatening *** this study,we used various patient datasets from a major hospital in the United States as prognostic factors for *** data was obtained by monitoring a total of 918 patients whose criteria for adults were 28-77 years *** this study,we present a data mining modeling approach to analyze the performance,classification accuracy and number of clusters on Cardiovascular Disease Prognostic datasets in unsupervised machine learning(ML)using the Orange data mining *** techniques are then used to classify the model parameters,such as k-nearest neighbors,support vector machine,random forest,artificial neural network(ANN),naïve bayes,logistic regression,stochastic gradient descent(SGD),and *** determine the number of clusters,various unsupervised ML clustering methods were used,such as k-means,hierarchical,and density-based spatial clustering of applications with noise *** results showed that the best model performance analysis and classification accuracy were SGD and ANN,both of which had a high score of 0.900 on Cardiovascular Disease Prognostic *** on the results of most clustering methods,such as k-means and hierarchical clustering,Cardiovascular Disease Prognostic datasets can be divided into two *** prognostic accuracy of CVD depends on the accuracy of the proposed model in determining the diagnostic *** more accurate the model,the better it can predict which patients are at risk for CVD.

关键词： Cardiovascular disease Data-driven analytics Data mining Hyperparameter optimization Orange data mining software Prognostic system Unsupervised machine learning

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Improvement of Localization Algorithm for Indoor and Outdoor Navigation of Autonomous Robots

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Journal of Institute of Control, Robotics and Systems 2025年第5期31卷 502-509页

作者： Cho, Joonhyuk Kim, Bongsang Moon, Heechang Industrial Convergence Interdepartmental Program Autonomous Vehicle Intelligent Robotics The Graduate School of Hongik University Korea Republic of Mechanical & System Design Engineering Hongik University Korea Republic of

Location estimation for waypoint-based autonomous driving robots primarily relies on SLAM (Simultaneous Localization and Mapping) and GNSS (Global Navigation Satellite System) technologies. GNSS performs well in open areas but struggles with signal issues, while SLAM offers high accuracy in feature-rich environments but faces challenges in open spaces. This study integrates SLAM and GNSS, enabling seamless switching between systems when one encounters difficulties. The combined system ensures consistency by aligning coordinate systems and directional data. Experiments in indoor, forest, and open environments demonstrate that the switching algorithm enables stable autonomous driving in diverse conditions, effectively leveraging the strengths of both systems. © ICROS 2025.

关键词： Global positioning system

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The Influence of Digital Adoption, Absorptive Capacity and Risk Management Implementation on Organizational Resilience: An Empirical Study in The Indonesian Banking Industry 2

The Influence of Digital Adoption, Absorptive Capacity and R...

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2nd IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2024

作者： Tjahyono, Boy Prabowo, Harjanto Alamsjah, Firdaus Hamsal, Mohammad Binus Graduate Program Binus Business School Research in Management Jakarta Indonesia Binus Graduate Program Binus Business School Industrial Engineering Jakarta Indonesia

ISBN: (纸本)9798350360523

One of the primary difficulties of Indonesia's banking sector is to ensure that it continues to develop in business, is robust, and can foresee new risks while enhancing governance, risk, and compliance. This study will determine the effect of risk management implementation, absorptive capacity, and digital adoption on organizational resilience. The survey method is being used as a research method, with targeted respondents from senior executives, including C-suites, senior vice presidents, and vice presidents. The results show that digital adoption and absorptive capacity impact risk management implementation and organizational resilience despite the limited research available in the Indonesian banking sector. The study will contribute to understanding how enterprise resilience is affected by risk management. This research has presented an opportunity for both banking management and policymakers to formulate strategies aimed at bolstering organizational resilience within the banking sector. These strategies could aid in navigating unforeseen and disruptive business environments. Furthermore, this study stands to expand the application of concepts such as organizational resilience and dynamic capacity theory, particularly within the banking industry of developing nations. © 2024 IEEE.

关键词： Risk management

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Industry 4.0 and Lean Manufacturing Contribute to the Development of the PDP and Market Performance? A Framework 1

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22nd IFIP WG 6.11 Conference on e-Business, e-Services and e-Society, I3E 2023

作者： Tardio, Paulo Roberto Schaefer, Jones Luís Gonçalves, Marcelo Carneiro Nara, Elpidio Oscar Benitez Industrial and Systems Engineering Graduate Program Pontifical Catholic University PR Curitiba Brazil

ISBN: (数字)9783031500404

ISBN: (纸本)9783031500398

To improve production processes, manufacturing companies have made efforts to implement Industry 4.0 technologies and spread the use of Lean Manufacturing (LM) tools. Besides, in addition to the improvements in production processes, these efforts have also been reflected in other issues such as in the Product Development Process (PDP) and Market Performance. In this sense, the objective of this article is to elaborate a conceptual framework covering the constructs of Industry 4.0, LM, and PDP, and to evaluate the importance of these constructs on Market Performance in manufacturing companies in the South of Brazil. The conceptual framework, elaborated with the help of high-impact articles in the area, was evaluated by managers of 111 manufacturing companies in the southern Brazil. The research showed that the implementation of LM tools is more related to the PDP than Industry 4.0 and that large companies have had more positive effects in the implementation of both Industry 4.0 technologies and LM tools. This research can serve as a guide for manufacturing companies, showing the benefits, challenges and opportunities regarding the implementation of LM and Industry 4.0 tools and technologies aiming to improve PDP and Market Performance. It is possible to observe through a structured and systemic framework. © IFIP International Federation for Information Processing 2023.

关键词： Lean production

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Prediction of Powerplant Performance by Machine Learning Technique 8

Prediction of Powerplant Performance by Machine Learning Tec...

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8th IEEE International Conference on Recent Advances and Innovations in engineering, ICRAIE 2023

作者： Gunawan, Fergyanto E. Wulandari, Rahmanda Wahyuningtyas, Dian Asrol, Mohammad Bina Nusantara University BINUS Graduate Program-Master of Industrial Engineering Industrial Engineering Department Jakarta11480 Indonesia Bina Nusantara University BINUS-ASO School of Engineering Business Engineering Program Industrial Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9798350315516

The IEEE Standard 762-1987 introduced a comprehensive set of 25 indices for reporting power plant reliability, availability, and productivity. The sheer number of indices can be impractical, and an univariate indicator is preferable for real-world applications. Developing a single indicator derived from the 25 indices is the work's main theme. This study addresses this issue using machine learning to consolidate these indices, ultimately classifying power plant performance into "performed"and "unperformed."Monthly performance data from 2020 were collected from 570 power plants in the Java-Sumatra interconnected electric system. These data were obtained from the Generation Availability Information System, a proprietary application owned by the Indonesia National Electric Power Company. Using the k-means clustering method, we classified the performance of these power plants. The clustering process was supplemented with the opinions of seven experts with extensive experience in the system. The comparison between machine learning classifications and expert opinions is presented. © 2023 IEEE.

关键词： IEEE Standards

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Tool Tracking System Design Using Quality Function Deployment Method for Vocational Education 8

Tool Tracking System Design Using Quality Function Deploymen...

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8th International Conference on Information Management and Technology, ICIMTech 2023

作者： Ferianto, Ibnu Priambada, Dwima Septiar Sahroni, Taufik Roni Afani, Randy Putra Bina Nusantara University Faculty of Engineering Industrial Engineering Department Jakarta11480 Indonesia Binus Graduate Program - Master of Industrial Engineering Bina Nusantara University Industrial Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9798350326093

Currently the process of lending tools in machining laboratories still uses the traditional method. it is considered inefficient and ineffective. Therefore, implementing a more modern tool lending system is one possible solution. In this study, the design and manufacture of a tool lending system was carried out by applying Radio Frequency Identification (RFID) technology and a website-based information system. The purpose of this research is to simplify the process of lending tools and simplify the process of tracking and collecting data on tools borrowed by students. The method used in this study is the Quality Function Deployment (QFD) method to determine the priority of the user's attribute requirements that will be used in the design and development of the system. System testing is carried out using the System Usability Scale (SUS) analysis. The result of this research was to produce a tool lending system called a tool tracking system that will completely automate the tool tracking procedure. This helps to better manage the fleet of tools efficiently. The system has been successfully developed and approved for use in machining laboratories at vocational education © 2023 IEEE.

关键词： Quality function deployment

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The Impact of Indonesian Managers' Digital Disruptive Skills on Organizational Resilience

The Impact of Indonesian Managers' Digital Disruptive Skills...

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2023 IEEE International Conference on industrial engineering and engineering Management, IEEM 2023

作者： Alamsjah, F. Asrol, M. Sukarta, S.M. Bina Nusantara University Binus Graduate Program - Master of Industrial Engineering Industrial Engineering Department Jakarta11480 Indonesia Binus Creates Jakarta11480 Indonesia

ISBN: (纸本)9798350323153

This article strives to study the direct effects of managers' disruptive skills to survive in a digital revolution assessed indirectly by organizational agility. In addition, the interactions of digital orientation are also assessed. A conceptual framework was devised to investigate the aforementioned correlations. Five hypotheses were developed and tested with data from 100 respondents who were affected by digital transformation and with positions one level above the manager level or higher. SmartPLS is used for analysis and to generate 500 bootstrap samples. This study makes three distinct contributions to the existing literature on digital transformation. First, digital disruptive skills have a direct impact on both organizational agility and organizational resilience. Second, leadership abilities have a strong beneficial impact on organizational agility and resilience across all three digital disruptive talents examined in this study. Finally, digital orientation has little effect on organizational resilience when it comes to digital disruptive talents. © 2023 IEEE.

关键词： Digital Disruptive Skills Digital Orientation Digital Transformation Organizational Agility Organizational Resilience

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BLOCKCHAIN TECHNOLOGY IMPLEMENTATION FOR HEALTHCARE PRIVACY DATA SYSTEMS IN THE UAE 50

BLOCKCHAIN TECHNOLOGY IMPLEMENTATION FOR HEALTHCARE PRIVACY ...

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50th International Conference on Computers and industrial engineering: Sustainable Digital Transformation, CIE 2023

作者： Alshamsi, Hessa Marei, Fatemaal Marwan, Tasnim Shamayleh, Abdulrahim Department of Industrial Engineering American University of Sharjah Sharjah United Arab Emirates Biomedical Engineering Graduate Program American University of Sharjah Sharjah United Arab Emirates Department of Industrial Engineering Biomedical Engineering Graduate Program American University of Sharjah Sharjah United Arab Emirates

ISBN: (纸本)9781713886952

Blockchain technology is being recognized as a significant solution to technical issues across various industries, including healthcare. In the healthcare sector, Blockchain has the potential to revolutionize processes such as transferring patient medical records, managing the medicine supply chain, and aiding healthcare researchers in unlocking genetic code. The United Arab Emirates (UAE) has emerged as a developed country actively exploring blockchain technology to enhance its healthcare sector. Despite efforts to improve healthcare in the UAE, integrating new technologies has been limited. The focus has primarily been on improving equipment and procedures rather than adopting innovative solutions. The growing population and increasing emphasis on medical tourism have also amplified the demand for advanced healthcare services. Therefore, immediate action is required to initiate significant developments in the healthcare sector. This research aims to highlight the importance and role of blockchain technology, specifically in the UAE healthcare sector. It seeks to improve the competence and privacy of healthcare data systems while addressing concerns related to centralization. The study presents recent findings concerning the initiatives and vision of the UAE government to establish a globally outstanding healthcare sector. It defines blockchain technology and emphasizes its positive impact on enhancing healthcare data systems. Furthermore, the research showcases various applications of blockchain technology that can be implemented in the healthcare sector. By demonstrating blockchain technology's benefits and potential applications, this research endeavors to encourage the strategic adoption of blockchain solutions in the healthcare sector. Such initiatives can pave the way for advancements in patient data systems and privacy. © 2023 Computers and industrial engineering. All rights reserved.

关键词： Blockchain

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Cost Analysis for Warranted Products Protected by Lemon Laws Considering Failure Interaction 6th

Cost Analysis for Warranted Products Protected by Lemon Laws...

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6th Asia Pacific Conference on Manufacturing System and the 5th International Manufacturing engineering Conference, APCOMS-IMEC 2022

作者： Alifin, Fakhri I. Cakravastia, Andi Iskandar, Bermawi P. Graduate Program in Industrial Engineering and Management Institut Teknologi Bandung Bandung Indonesia Department of Industrial Engineering Universitas Singaperbangsa Karawang Karawang Indonesia Department of Industrial Engineering Institut Teknologi Bandung Bandung Indonesia

ISBN: (纸本)9789819912445

This study develops warranty cost models for a warranted product under the lemon laws protection. The product considered in this study is a multi-component system consisting of critical and non-critical components. The Failure of either component can cause the product to fail. The product is declared a lemon if recurrent failures of the critical component occur—i.e., the number of the failures reaches the threshold value, k (e.g., four failures). Furthermore, this study assumes that a failure of the critical component can occur naturally or induced by a failure of the non-critical component. Hence, two types of failures are considered—i.e., a natural failure and an induced failure. Whenever a lemon is declared, the customers can opt for either (i) a refund or (ii) a replacement warranty claim. Hence, this paper provides the warranty cost models for the two cases—(i) refund and (ii) replacement then encounters the optimal lemon law period that minimizes the expected warranty cost rate. The numerical examples are provided to illustrate the expected warranty cost and the optimal lemon law period. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Cost benefit analysis

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Random Number Generator for Securing Data Exchange in Smart Factory: Recent Trends and Best Practices 3

Random Number Generator for Securing Data Exchange in Smart ...

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3rd International Conference on Computer Technologies, ICCTech 2024

作者： Sama, Andi Meyliana Heryadi, Yaya Sahroni, Taufik Roni Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Information System Information System Department Jakarta11480 Indonesia BINUS Graduate Program-Doctor of Computer Science Jakarta Computer Science Department Jakarta11530 Indonesia Bina Nusantara University BINUS Graduate Program - Master of Industrial Engineering Industrial Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9798350395419

IT/OT convergence in the form of a Cyber-Physical System (CPS) presents an opportunity to apply recent Information Technology (IT) advancements to Operational Technology (OT). The IT/OT convergence introduces cyber security threats for OT. The OT communication protocols, for example, have limited or no security capabilities for securing data exchange beyond basic authentication. The RNG (Random Number Generator) function is crucial in PLC for producing the encryption keys or the initial seed for security algorithms. The software-based PRNG (Pseudo RNG) is the most common approach for RNG in OT, instead of hardware-based RNG. This study provides a systematic literature review of the most recent evidence in digital transformation to secure data exchange in smart factories, within OT, or across OT and IT settings. It does this by looking at the PRNG on PLC and identifying the most recent trends and best practices. The findings include up-to-date data on author countries' distribution, published journals, research trends, industries, and industry types. The findings also address whether data flow is encrypted or shared in plaintext to ensure secure data transfer between IT and legacy OT environments. This paper concludes that while there is known RNG implementation in the actual embedded system in ICS, there is no evidence in the literature for using RNG in ICS networks for PLC implementation to secure data transfer with encryption. © 2024 IEEE.

关键词： Data transfer

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