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检索条件"任意字段=2012 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2012"

共 5022 条记录，以下是21-30 订阅

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Empowering Small and Medium Enterprises with Data Analytics for Enhanced Competitiveness 13

Empowering Small and Medium Enterprises with Data Analytics ...

引用

13th ieee international conference on control system, computing and engineering, iccsce 2023

作者： Mosbah, Aissa Ali, Musab A. M. Tahir, Nooritawati Md Dhofar University College of Commerce and Business Administration Salalah Oman University of Technology and Applied Sciences Ibri Oman International Information Technology University Department of Computer Engineering and Information Security Almaty Kazakhstan Universiti Teknologi Mara School of Electrical Engineering College of Engineering Malaysia Malaysia

ISBN: (纸本)9798350323184

In today's competitive landscape, Small and Medium-sized Enterprises (SMEs) are increasingly embracing business data analytics to gain valuable insights and make informed decisions. However, the true essence of big data lies not only in its volume but also in the analysis process and the derived insights that aid managers in making effective business choices. Despite this, limited knowledge exists regarding SMEs' utilization of data analytics and its potential in facilitating informed decision-making. Therefore, this paper aims to elucidate the concept of business data analytics within the context of SMEs and outline the essential requirements for its effective implementation, enabling SMEs to leverage data analytics for enhanced competitiveness. It is proposed that the foundation of a successful data analytics system for SMEs should encompass four key elements: data, people, technology, and process. The degree to which data analytics contributes to a firm's competitiveness is largely influenced by four factors: data quality, well-defined objectives, the caliber of analytic tools and techniques, and analytical skills. Data generates information and insights, which in turn foster knowledge that ultimately leads to wisdom. However, due to limited resources, SMEs may be less inclined to engage in advanced predictive and prescriptive analytics compared to larger firms. © 2023 ieee.

关键词： Decision making

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Development and Evaluation of Wireless Oxygen Saturation Monitoring system 13

Development and Evaluation of Wireless Oxygen Saturation Mon...

引用

13th ieee international conference on control system, computing and engineering, iccsce 2023

作者： Karia, Muhammad Amar Haziq Mohd Hamid, Shabinar Abdul Abdullah, Samihah Muhammad, Zuraida Fadhlullah, Solahuddin Yusuf Leh, Nor Adni Mat Universiti Teknologi Mara Cawangan Pulau Pinang Electrical Engineering Studies College of Engineering Pulau Pinang Permatang Pauh13500 Malaysia Inti International College School of Engineering and Technology Penang Malaysia

ISBN: (纸本)9798350323184

Oxygen saturation (SpO2) is a critical parameter used to measure the amount of oxygen bound to hemoglobin in the bloodstream. Continuous monitoring and accurate records on the patient's SPO2 are crucial to assist doctors in assessing the effectiveness of treatment and the need for supplemental oxygen. Therefore, this project proposes the development of a pulse oximeter device using dual RFID communication to enable continuous, real-time, and wireless data recording. The reading of SPO2 can vary in various situations. The evaluation to investigate significant factors that could affect the accuracy of SpO2 readings is carried out using the Design of Experiment and Analysis of Variance. The statistical analysis showed that the types of fingers and nail substances are the main factors that influence the accuracy of SpO2. The main effect plot shows that the SPO2 reading on the nail with oil substance and thumb gives the highest accuracy compared to other types of substance and types of fingers, respectively. © 2023 ieee.

关键词： Oxygen

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Fusing Frontal Face Recognition Using Multi View Cameras 13

Fusing Frontal Face Recognition Using Multi View Cameras

引用

13th ieee international conference on control system, computing and engineering, iccsce 2023

作者： Rashidan, M.A. Sidek, S.N. Al-Samman, M.M. International Islamic University Malaysia Department of Mechatronics Kulliyyah of Engineering Kuala Lumpur Malaysia

ISBN: (纸本)9798350323184

The recognition of faces in videos has recently gained considerable attention, but the recognition process executed on a single camera has limitations, especially when dealing with uncooperative subjects, changes in body posture, or self-occlusion. These challenges are particularly relevant in the context of studying facial analysis in children with Autism Spectrum Disorder (ASD). Therefore, the use of multiple cameras in a face recognition system is proposed to overcome these limitations. Facial image realignment was employed in the automatic face recognition process. To achieve this, the Kanade-Lucas-Tomasi (KLT) algorithm was used to track facial features, and the RANSAC algorithm was utilized to estimate the homography transformation for realigning the multi-view input images. To assess and compare the similarity of the fused image, the normalized cross-correlation (NCC) was employed. The resulting fused image was obtained based on the extracted pose of the face. The results demonstrate the efficacy of the method, achieving an accuracy of 94.5% for typically developed children and 87.3% for ASD children. © 2023 ieee.

关键词： Face recognition

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Frontal Face Tracking in the Thermal Infrared Imaging for Autism Spectrum Disorder Children 13

Frontal Face Tracking in the Thermal Infrared Imaging for Au...

引用

13th ieee international conference on control system, computing and engineering, iccsce 2023

作者： Rashidan, M.A. Sidek, S.N. Yusof, H.M. Ghazali, A.S. Rusli, N. International Islamic University Malaysia Kulliyyah of Engineering Department of Mechatronics Jalan Gombak Kuala Lumpur53100 Malaysia ProStrain Technologies 1-10 Hive 12 Taman Teknologi Mranti Bukit Jalil Kuala Lumpur57000 Malaysia

ISBN: (纸本)9798350323184

The research and application of therapeutic robotics for children have gained significant attention. This study introduces a system for emotion recognition in Autism Spectrum Disorder (ASD) children that utilizes infrared thermal imaging cameras to capture the frontal facial images. The paper focuses on the development to automate, recognize and track the subjects frontal face using the Shape-Adapted Mean Shift algorithm (SAMShift) applied to thermal images. This system targets the identification of affective states in ASD children and employs non-invasive thermal imaging instead of invasive sensor patches. By integrating tracking and affective state analysis within a single modality, the system addresses the limitations of traditional visual-based systems, which often suffer from invasiveness due to the use of sensor patches, difficulty in automating and tracking facial features, and challenges in accurately identifying affective states. The SAMShift algorithm, implemented in the LabVIEW® vision module environment, is utilized for tracking the frontal face image. Experimental results demonstrate the effectiveness of the proposed method, achieving an average accuracy of 89.20% and an average precision of 95.40%. This research contributes to advancing the field of therapeutic robotics for children with ASD by providing an automated, non-invasive, and accurate approach to emotion recognition. © 2023 ieee.

关键词： Emotion Recognition

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Output Feedback Stabilization of Nonholonomic Wheeled Mobile Robot Using Backstepping control 12

Output Feedback Stabilization of Nonholonomic Wheeled Mobile...

引用

12th ieee international conference on control system, computing and engineering, iccsce 2022

作者： Rabbani, Muhammad Junaid Memon, Attaullah Y. PN Engineering College National University of Sciences and Technology Department of Electronics and Power Engineering Karachi Pakistan

ISBN: (数字)9781665483391

ISBN: (纸本)9781665483391

A novel output feedback posture stabilization of wheeled mobile robot (WMR) is presented to overcome the challenges faced by posture stabilization of WMR. A generalized normal form of WMR is developed by a suitable change of coordinates via input-output feedback linearization approach, with the restriction of nonzero initial condition of orientation angle. The internal dynamics is in a strict feedback form that provides an ease to implement a regular integral backstepping control technique. The control law achieves asymptotic stabilization of both the internal and external dynamics of mobile robot. The control design of state feedback is further enhanced to output feedback control utilizing a full order high gain observer. It is shown that estimated states converge to true states rapidly with good transient behavior. Stability analysis of the overall system is proved using Lyapunov method. © 2022 ieee.

关键词： Mobile robots

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Design a Speed control for DC Motor Using an Optimal PID controller Implementation of ABC Algorithm 12

Design a Speed Control for DC Motor Using an Optimal PID Con...

引用

12th ieee international conference on control system, computing and engineering, iccsce 2022

作者： Tajudin, Aimi Idzwan Izani, Muhammad Affi Daneal Samat, Ahmad Asri Abd Omar, Saodah Idin, Mohamad Adha Mohamad Universiti Teknologi MARA Centre for Electrical Engineering Studies Malaysia

ISBN: (数字)9781665483391

ISBN: (纸本)9781665483391

The project purpose to implement Artificial Bee Colony (ABC) algorithm optimization technique for controlling the speed of the DC motor. The separately excited DC motor had been used to analyze the performance of the proposed technique. The boost converter has been selected to supply the required voltage to the terminal voltage of the DC motor. The PID controller was selected to control the desired performance of the converter. The determination of the best parameter is the main issue for this controller. The ABC algorithm was implemented to enhance the system performance by optimizing the PID gains. The objective function of error which is Integral-weight Time Absolute Error (ITAE) was used to minimize the index speed error of the motor. The proposed technique shows its capability to improve the speed response of the DC motor. Simulation model was developed using MATLAB/Simulink. © 2022 ieee.

关键词： DC motors

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CNN Comparative Study for Apple Quality Classification 12

CNN Comparative Study for Apple Quality Classification

引用

12th ieee international conference on control system, computing and engineering, iccsce 2022

作者： Ibrahim, Muhammad Syafiq Hamid, Shabinar Abdul Muhammad, Zuraida Leh, Nor Adni Mat Abdullah, Samihah Bakar, Siti Juliana Abu Osman, Muhammad Khusairi Fadhlullah, Solahuddin Yusuf Universiti Teknologi MARA Centre for Electrical Engineering Studies Penang Malaysia School of Engineering and Technology INTI International College Penang Malaysia

ISBN: (数字)9781665483391

ISBN: (纸本)9781665483391

A reliable and efficient automated fruit grading process is needed to meet the market's increased demand for good quality fruits. Automated systems based on image processing technology are being developed to reduce reliance on manual expertise, which is often time-consuming, expensive, and biased. The propose of this paper is to construct and evaluate different types of CNN models, including conventional CNN, GoogLeNet and AlexNet, for categorising fresh and rotten appearances using a dataset of apple images. All the datasets had performed the operations of pre-processing steps with scaling, rotating, and cropping. All models were trained and tested using the datasets provided by the KAGGLE network. The accuracy and loss performance of all the models are measured. The result shows that the GoogLeNet achieved 100% accuracy, which has better performance compared to the AlexNet and conventional CNN. Hence, the GoogLeNet model has the potential for integration into an automatic fruit grading system. © 2022 ieee.

关键词： Fruits

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Speed control of SEDC Motor Using Artificial Neural Network 12

Speed Control of SEDC Motor Using Artificial Neural Network

引用

12th ieee international conference on control system, computing and engineering, iccsce 2022

作者： Samat, Ahmad Asri Abd Jaafar, Muhammad Irfan Bin Ahmad Tajudin, Aimi Idzwan Salim, Nur Ashida Daud, Kamarul Azhar Kamarudin, Nornaim Universiti Teknologi MARA Centre for Electrical Engineering Studies Malaysia Putra Walk Business Centre Seri Kembangan Selangor 43300 Malaysia School of Electrical Engineering College of Engineering Universiti Teknologi MARA Selangor Shah Alam40450 Malaysia

ISBN: (数字)9781665483391

ISBN: (纸本)9781665483391

This project designed the speed control of a separately excited direct current (DC) motor by using an Artificial Neural Network (ANN). Any conventional controller such as proportional-integral (PI) can be used to control the speed of a DC Motor. However, the limitation of the conventional controller in controlling the speed of the dc motor is inaccuracy in the ability to obtain the actual speed and maintain the stability of the motor speed in the dynamic condition. Thus, the ANN controller had been introduced to solve the problem involving the limitation of another conventional controller. The neural network is used in this project to control or estimate the motor speed by training the neural network and getting the desired result using MATLAB/SIMULINK software. In this project, the ANN has proven its ability to control motor speed compared to the PI controller effectively and has good performance in a nonlinear system. The simulation results show the advantages and efficiency of an ANN with minimum speed error which is approximately zero rpm. © 2022 ieee.

关键词： Neural networks

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Facial Expression Electric Wheelchair control Instruction Using Image Processing 12

Facial Expression Electric Wheelchair Control Instruction Us...

引用

12th ieee international conference on control system, computing and engineering, iccsce 2022

作者： Sobri, Muhammad Faiz Ahmad Hussain, Zakaria Yahaya, Saiful Zaimy Boudville, Rozan Aziz, Noraiza Aqilah Abdul School of Electrical Engineering College of Engineering Universiti Teknologi MARA Malaysia

ISBN: (数字)9781665483391

ISBN: (纸本)9781665483391

Tetraplegia is a type of paralysis that affects upper and lower limbs due to damage of spinal cord or brain. This condition causes difficulty to move and most of the time caretaker is needed to help the patients. This project proposed the design and implementation of an image processing technique in capturing and categorizing different facial gesture and use it as control instructions for electric wheelchair. The aim was to reduce the dependency to caretaker especially for mobility oftetraplegia patient. The deep learning Haar Cascade Classifier identify the expression of a face through image processing in livevideo capture. The Open Computer Vision (OpenCV) in Python was used to detect, recognize, and analyze the facial expression. Convolution Neural Network (CNN), a deep learning operation will act as trainer that analyze an open-source data to create a model as reference for the facial expression recognition. In orderto make the system operated as a standalone system, the Raspberry Pi module that connects with Pi Camera was used as the platform to capture the live video, perform processing, and produce the output control that give instructions to move such as forward, right, left and stop. Based on the analysis of the system performance, the system was capable to produce high accuracyof detection and correctly produce the electric wheelchair controlinstruction according to the facial expressions. © 2022 ieee.

关键词： Image classification

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Liver Tumour Segmentation based on ResNet Technique 12

Liver Tumour Segmentation based on ResNet Technique

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12th ieee international conference on control system, computing and engineering, iccsce 2022

作者： Sirco, Adelisa Almisreb, Ali Tahir, Nooritawati Md Bakri, Jamil International University of Sarajevo Faculty of Engineering and Natural Sciences Sarajevo Bosnia and Herzegovina College of Engineering Universiti Teknologi MARA Selangor Malaysia Universiti Teknologi MARA Selangor Malaysia Universiti Teknologi MARA Selangor Malaysia Worldwide Green Berhad Selangor Shah Alam Malaysia

ISBN: (数字)9781665483391

ISBN: (纸本)9781665483391

It is known that the sixth most common cancer worldwide is liver cancer and CT scans are commonly used to diagnose liver cancer. Hence in this study, deep learning techniques specifically the ResNet models are used to extract the liver and tumour from the CT scans. Here, four liver segmentation methods are used based on 130 CT datasets namely the ResNet-18, ResNet-34, ResNet-50, and ResNet-101. Each model is evaluated and validated based on their training and testing accuracy, number of epochs, valid loss and train loss. Initial results showed that the highest accuracy is contributed by ResNet-34 with 99.2% accuracy and next is ResNet-50. Additionally, ResNet-101 is the most efficient network model whilst ResNet-18 is the most rapid. These findings proved that the deep learning can be used for segmentation of liver tumour based on the CT scan images. © 2022 ieee.

关键词： Tumors

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