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Fuzzy Risk Model for Research and Development department in Clinical Laboratory 9

Fuzzy Risk Model for Research and Development Department in ...

引用

9th IEEE International Conference on Computing, engineering and Design, ICCED 2023

作者： Legowo, Nilo Sarjdono, Wahyu Susanto, Eddy Utama, Ditdit Nugeraha Bina Nusantara University BINUS Graduate Program Master of Information Systems Management Information Systems Management Department Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350370126

Information security risk is of utmost importance and a crucial concern, particularly within a clinical laboratory responsible for managing sensitive public health information. Various endeavors have been undertaken by institutions to tackle this pressing challenge effectively. This research seeks to develop a computer-based decision model for assessing information security risks. The model is scientifically constructed using the fuzzy logic method as its core approach and designed through an object-oriented approach. Impressively, the model successfully simulates 31 risk scenarios with an accuracy rate of 93.55%. © 2023 IEEE.

关键词： Fuzzy logic

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RUL Estimation for Power Electronic Devices Using RNNs

RUL Estimation for Power Electronic Devices Using RNNs

引用

2024 Prognostics and System Health Management Conference, PHM 2024

作者： Cai, Congrui Lu, Zhonghai School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Embedded Systems Master Program Sweden School of Electrical Engineering and Computer Science Department of Electrical Engineering KTH Royal Institute of Technology Sweden

ISBN: (纸本)9798350360585

Recurrent Neural Networks (RNNs) are commonly used in data-driven approaches to estimate the Remaining Useful Lifetime (RUL) of power electronic devices. RNNs are preferred because their intrinsic feedback mechanisms are better suited to model time-series data. However, the impact of RNN complexity on estimation accuracy is rarely discussed in the literature. This issue is important because choosing a lower-complexity model that delivers the same or similar performance as a higher-complexity model can increase implementation efficiency. In the paper, we use three RNN models, namely, the vanilla version, LSTM (Long Short Term Memory) and GRU (Gated Recurrent Unit) to conduct RUL estimation for power electronic devices. We use two accelerated aging datasets, one dataset targeting the package failure of MOSFETs, and the other dataset targeting package failure of power diodes. Our study shows that a lower-complexity RNN does not necessarily deliver a lower performance. Similarly, a higher-complexity model does not assure a higher performance. As such, our work highlights the importance of selecting a proper neural network for RUL estimation not biased towards complex models. This is especially useful and important for implementing such RUL estimation techniques in embedded resource-constrained and speed-limited computins platforms. © 2024 IEEE.

关键词： Long short-term memory

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Hoax Classification in Imbalanced Datasets Based on Indonesian News Title using RoBERTa 3

Hoax Classification in Imbalanced Datasets Based on Indonesi...

引用

3rd International Conference on Artificial Intelligence and Data sciences, AiDAS 2022

作者： Muliono, Yohan Gaol, Ford Lumban Soewito, Benfano Warnars, Harco Leslie Hendric Spits School of Computer Science Bina Nusantara University Binus Graduate Program - Doctor of Computer Science Computer Science Department Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program - Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (数字)9781665491648

ISBN: (纸本)9781665491648

Hoaxes are something that can not be avoided, especially in Indonesia, where the literacy rate in Indonesia is quite low, they are easy to believe in news without doing fact check. The worst thing is that news that is trusted by the public may not be read completely through the entire content. They believe, from the title alone could already covers the entire content of the news. Media in the other side, are also competing to make controversial titles so that their traffic is improved. The research that will be carried out by us is where we can classify a news whether it is a fact or a hoax from the title alone. The RoBERTa (A Robustly Optimized BERT Pretraining Approach) model will be used in this study, because in several previous studies RoBERTa has proven to be good for classification. The accuracy achieved in this study also reached 99.52% with an accuracy validation of 93.84% which shows that even with an imbalanced dataset the classification shows a promising result by using the RoBERTa model which data is balanced using the undersampling method. © 2022 IEEE.

关键词： Classification (of information)

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Synthesis of Robust PID Controllers with Disturbance Attenuation Performance for Polytopic Uncertain Multi-Input Multi-Output Systems 3

Synthesis of Robust PID Controllers with Disturbance Attenua...

引用

3rd IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2024

作者： Ito, Yuki Asada, Daiki Sawato, Hayate Shibuya, Kouki Hoshi, Yoshikatsu Oya, Hidetoshi Tokyo City University Graduate School of Integrative Science and Engineering Tokyo Japan Tokyo City University The Department of Computer Science Tokyo Japan

ISBN: (纸本)9798331540319

This paper proposes a new parameter adjustment law for robust PID control systems with disturbance attenuation performance for polytopic uncertain multiple-input multiple-output (MIMO) systems. In the proposed design approach, the problem of designing the parameter adjustment law for robust PID control systems is reduced to a design problem of static output feedback controllers for uncertain MIMO systems. In this paper, we show that the sufficient conditions for the existence of the proposed parameter adjustment law for the robust PID control system can be reduced to the solvability of linear matrix inequalities (LMIs). Finally, a simple numerical example is provided to demonstrate the effectiveness of the proposed robust PID control system. © 2024 IEEE.

关键词： MIMO systems

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Testing Approach for IoT System (Case Study: Air Quality Monitoring System) 8

Testing Approach for IoT System (Case Study: Air Quality Mon...

引用

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

作者： Rochadiani, Theresia Herlina Soeparno, Haryono Gaol, Ford Lumban Arifin, Yulyani Bina Nusantara University Binus Graduate Program - Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia Pradita University Informatics Department Tangerang15810 Indonesia

ISBN: (纸本)9798350326093

The Internet of Things (IoT) was evaluated as part of this study. The IoT system in this study is the air quality monitoring system. The system consists of three layers, three end devices with air quality monitoring sensors as the perception layer, the LoRaWAN network as the network layer, and the monitoring website as the presentation layer. Before being made available to the public, IoT hardware and software must undergo testing. For IoT systems, there are no established standards or quality criteria. This study's goal is to evaluate the methodology for an air quality monitoring system. Website speed is measured using Pingdom tools. The website received a performance grade of B. Pingdom offers advice for enhancing website performance. Sucuri is utilized as a security test tool to evaluate the website's security, and consequently, no malware was discovered. The latency and data dependability are monitored to assess the system's performance fully. The outcome demonstrates that all system components consistently and accurately receive data with a latency of less than 1 s. © 2023 IEEE.

关键词： Internet of things

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Enhancing Forest Fire Detection: Utilizing VGG16 for High-Accuracy Image Classification and Machine Learning Integration 8

Enhancing Forest Fire Detection: Utilizing VGG16 for High-Ac...

引用

8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024

作者： Tan, Muhammet Bakir, Halit Sivas University of Science and Technology Institute of Graduate Studies Sivas Turkey Sivas University of Science and Technology Department of Computer Engineering Sivas Turkey

ISBN: (纸本)9798331531492

Forest fires cause significant problems for nature, communities. They damage forests, animals' homes, and places where people live. The bad effects of forest fires go beyond just hurting the air, water, and animals. They also make climate change worse and mess up the balance of nature for a long time. In our efforts to address this significant issue, we utilize trained Convolutional Neural Networks (CNNs) algorithm VGG16 model to classify images containing fire and smoke versus non fire images. To enhance the training performance and the model's ability to generalize to unseen data, we curated a dataset comprising approximately 12,000 images from each category. We proposed using the features extracted the VGG16 model for training a simple neural network and multiple machine learning algorithms. Following the training process of the neural network model, our model achieved a training accuracy of 98.4231% and a validation accuracy of 99.0717%. Subsequently, to assess the robustness of our model, we subjected the output layer of our trained model to 13 different machine learning algorithms. Remarkably, all 6 models surpassed a performance threshold of 99% across all metrics. © 2024 IEEE.

关键词： Premixed flames

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Analysis of Biosignal Data and Development of Estimation Systems for Artificial Insemination Timing of Cows 3

Analysis of Biosignal Data and Development of Estimation Sys...

引用

3rd IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2024

作者： Nouchi, Shugo Noma, Hiroto Harada, Takaya Kobana, Ryota Oya, Hidetoshi Graduate School of Integrative Science and Engineering Tokyo City University Tokyo Japan Tokyo City University Department of Computer Science Tokyo Japan

ISBN: (纸本)9798331540319

In this paper, we propose an estimation system for Artificial Insemination (AI) timing based on analysis of the normal fluctuations for the body surface temperature (ST) of cows. Firstly, ST data is normalized and an approximate waveform via the fundamental waveform synthesis method is generated. Next, a reconstructed waveform which remove circadian rhythms and the high frequency noise is calculated, and feature parameters are extracted from the obtained reconstructed waveform. Moreover, estimation system for AI timing is developed by utilizing Maha-lanobis squared distance. In this paper, the proposed estimation system is presented and its effectiveness is evaluated. © 2024 IEEE.

关键词： Frequency estimation

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Synthesis of Decentralized Variable Gain Robust Control Giving Consideration to Transient Behavior for Uncertain Large-Scale Serially Connected Systems via Piecewise Lyapunov Functions 3

Synthesis of Decentralized Variable Gain Robust Control Givi...

引用

3rd IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2024

作者： Sawato, Hayate Asada, Daiki Takahashi, Haruto Shibuya, Kouki Hoshi, Yoshikatsu Oya, Hidetoshi Graduate School of Integrative Science and Engineering Tokyo City University Tokyo Japan Tokyo City University The Department of Computer Science Tokyo Japan

ISBN: (纸本)9798331540319

In this paper, a design method for decentralized robust controllers giving consideration to transient behavior for uncertain large-scale serially connected systems via piecewise Lyapunov functions (PLFs) is proposed. The proposed control law consists of a state feedback law and a compensation input with uniformly continuous functions. In our approach, chattering phenomenon in the control input is avoided by utilizing uniformly continuous functions. In this paper, we show that a sufficient condition for the existence of the proposed decentralized variable gain robust controller is reduced to linear matrix inequalities (LMIs). © 2024 IEEE.

关键词： Decentralized control

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Toward Learning Factory for Industry 4.0: Virtual Reality (VR) for Learning Human–Robot Collaboration 1

引用

International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2022

作者： Ariansyah, Dedy Colombo, Giorgio Pardamean, Bens Bioinformatics and Data Science Research Centre Bina Nusantara University Jakarta11480 Indonesia Department of Mechanical Engineering Politecnico di Milano Milan20156 Italy Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

Industry 4.0 will bring not only transformation to the manufacturing technologies but also to the profile of the workforce. Education system should be revised to prepare the future graduates embracing the knowledge of the ongoing revolution. Initiatives on the modification of curriculum and tools to deliver the concepts of Industry 4.0 must be taken. This paper examines limitations of current engineering tools and proposes a virtual reality (VR)-based learning platform to support the teaching and learning activity for Industry 4.0, focusing on the design of Human–robot Collaboration (HRC). The development process began with the identification of the general Intended Learning Outcomes (ILOs) which were extracted from the review of the HRC design issues, followed by the evaluation of the current teaching tool. From these results, the new requirements of the tools to achieve ILOs are redefined. The implementation of the system is demonstrated to show the feasibility of the proposed learning platform. This workflow can serve as initial development of another learning platform for the other innovative concepts that form the building blocks of Industry 4.0. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Industry 4.0

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A Robust Dynamic Output Feedback Control with Adaptive Compensation Inputs for a Class of Uncertain Switched Linear Systems 3

A Robust Dynamic Output Feedback Control with Adaptive Compe...

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3rd IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2024

作者： Takahashi, Haruto Asada, Daiki Sawato, Hayate Shibuya, Kouki Hoshi, Yoshikatsu Oya, Hidetoshi Graduate School of Integrative Science and Engineering Tokyo City University Tokyo Japan Tokyo City University The Department of Computer Science Tokyo Japan

ISBN: (纸本)9798331540319

This paper proposes a design method of robust dynamic output feedback controllers for a class of uncertain switched linear systems. The proposed controller consists of a switching rule, a dynamic output feedback controller with an adaptive compensation input, and the adaptive compensation input is tuned by updating laws. In this paper, we show that sufficient conditions for the existence of the proposed robust output feedback control system are given in terms of linear matrix inequalities (LMIs). © 2024 IEEE.

关键词： Linear matrix inequalities

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