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Reverse Engineering Artificial Knee Joint using 3D Scanning 3

Reverse Engineering Artificial Knee Joint using 3D Scanning

引用

3rd IEEE international Biomedical Instrumentation and Technology conference, IBITeC 2023

作者： Setyoadi, Yuris Ismail, Rifky Jamari, J. Bayuseno, A.P. Novriansyah, Robin Prawibowo, Hartanto Universitas Diponegoro Mechanical Engineering Department Semarang Indonesia Pgri University Mechanical Engineering Department Semarang Indonesia Center for Bio-Mechanics Bio-Material Semarang Indonesia Dr. Kariadi Hospital Department of Orthopaedic and Traumatology Semarang Indonesia

ISBN: (纸本)9798350302424

The knee joints are regarded as one of the parts of the human body in which the thigh bone (femur) to the shin bone (tibia) is linked. The field of engineering involves the processes needed to design, manufacture, assemble, and maintain products and systems. Traditional forward engineering transforms them into physical products or Reverse Engineering (RE) methods. This section presents the methodology and results from the physical experiment on Artificial Knee Joint (AKJ), which was reverse-engineered using a handheld, non-contact 3D laser scanner. The method used compares AKJ coating using tape and AESUB 3D Scanning Spray. The results of measurements with laser scanners are in the form of point clouds. Furthermore, data processing needs to be carried out as an inspection process. AKJ geometry inspection process with 3D laser scanner tool by comparing femoral scan results using tape and AESUB 3D Scanning Spray. This article reported a case study conducted to investigate the possibilities and challenges of 3D scanning technology for reverse engineering. The case study results are compared with those reported in the literature. The technology generally provides opportunities to conduct RE by scanning the object and transforming it into CAD with different surface reconstruction techniques. © 2023 IEEE.

关键词： data handling

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Uncovering Bullying on Social Media Platforms: A Comprehensive Study of Machine Learning Classifiers for Cyberbullying Detection 3rd

Uncovering Bullying on Social Media Platforms: A Comprehensi...

引用

3rd international conference on Trends in Electronics and Health Informatics, TEHI 2023

作者： Hamim, Hasibul Uddin, Khandaker Mohammad Mohi Mim, Mst. Nishat Tasnim Mostafiz, Rafid Based, Md. Abdul Department of Computer Science and Engineering Dhaka International University Dhaka1205 Bangladesh Department of ComputerScience and Engineering Southeast University Dhaka1208 Bangladesh Institute of Information Technology Noakhali Science and Technology University Noakhali Bangladesh

ISBN: (纸本)9789819739363

One of the most delicate concerns is cyberbullying due to today’s worldwide web advancement. Bullying may contribute to severe consequences, including mental health issues, academic performance challenges, and job dropout. It can also instill hatred in individuals or communities, making cyberbullying prevention critical. Our main goal in this paper is to mitigate the impact of cyberbullying and contribute to fostering a healthier Internet environment where individuals can interact without fear of unwarranted criticism. We propose a proactive approach involving early detection mechanisms. In this study, we employ a comprehensive analysis of tweets using multiple factors. The data is preprocessed using machine learning methods and natural language processing (NLP), followed by Term Frequency Inverse Document Frequency (TF-IDF) and Count Vectorizer. Several machine learning models, including Light Gradient Boosting Machine (LightGBM) and 12 others, are evaluated. The dataset comprises over 47,000 tweets from various perspectives. Our analysis indicates that the LightGBM classifier outperforms other models with an accuracy of 94.24%, precision of 95%, recall of 94%, and an F1-score of 94%. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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Preliminary Study on Structure of Carbon Derived from Palm Oil Shell 3

Preliminary Study on Structure of Carbon Derived from Palm O...

引用

3rd international Symposium on Physics and Applications 2023, ISPA 2023

作者： Wardhani Mas'Udah, Kusuma Tiara Permatasari, Gabriella Astuti, Fahmi Asih, Retno Darminto, Darminto Departement of Physics Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Suarabaya Indonesia Department of Physics Faculty of Engineering University of Pembangunan Nasional Veteran Jawa Timur Indonesia

Palm shells are waste that is produced every year due to the large demand for palm oil. The potential for carbon derivatives in palm shell charcoal waste that can be extracted is more like activated carbon. Therefore, this research aims to provide an explanation of the ability of palm shell charcoal carbon as a residual component of palm oil processing that is affordable and abundantly available, which if maximized properly will be the forerunner to the development of technology that has added value. The capabilities of Palm Shell Charcoal can be applied for technical applications with further development. It is hoped that this study will provide initial information for scientists and policy makers in the fields of environmental conservation and technology. Palm shell charcoal (ACKS) that has been washed, dried and made into powder is subjected to DSC-TGA, FTIR, Xrd, SEM-EDX testing. The Xrd results show that there is a main broad peak that appears around the 2θ ∼23° angle which corresponds to the (002) plane and also a narrow peak appears at the 26° angle which indicates graphite growth. Meanwhile, the FTIR results show that many of the bonds formed are C=O, C-O, C=C and O-H bonds which indicate the presence of hard carbon. © Published under licence by IOP Publishing Ltd.

关键词： Palm oil

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Load Disaggregation using Graph signal processing

Load Disaggregation using Graph Signal Processing

引用

Sustainable Energy and Future Electric Transportation (SEFET), international conference on

作者： C. Baskar S. Charles Raja S. Padmavathi Dept. of EEE Thiagarajar College of Engineering Madurai Dept. of I.T Thiagarajar College of Engineering Madurai

In the era of the smart grid, energy disaggregation systems Non-Intrusive Load Monitoring(NILM) become the leading edge in the domain of Demand Side Management(DSM) which intends to provide a path for consumers to grab knowledge about their overall energy usage patterns and to devise appropriate energy strategies with limited smart meter installations. This paper proposes an initiative method on NILM called Non-Intrusive Device Level Load Classification(NIDLC), which classifies the appliances based on the load pattern using a technique of Graph signal processing(GSP). The data for load classification is collected from the embedded system built with the raspberry pi and made available in the Applied Electronics Laboratory of the EEE department of Thiagarajar College of Engineering, Madurai. The outcome of the proposed disaggregation is found to be significantly better than the values that were anticipated from the conventional process.

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Fuzzy Logic-Based Design Optimization and Economic Planning of a Microgrid for a Residential Community in Bangladesh

Fuzzy Logic-Based Design Optimization and Economic Planning ...

引用

international conference on Robotics,Electrical and signal processing Techniques (ICREST)

作者： Sayeed Hasan Md. Rifat Hazari Mohammad Abdul Mannan Department of Electrical and Electronics Engineering American International University-Bangladesh (AIUB) Dhaka Bangladesh

Hybrid renewable energy systems are becoming more predominant because of climate change and the overconsumption of natural fuels. Proper utilization of renewable resources can uplift energy-deprived regions while also contributing to a nation's economic growth. However, effective system planning and resource assessment are essential for effective utilization. In that regard, the study proposes a hybrid microgrid design for a remote island in Bangladesh. The proposed system comprises solar photovoltaics, wind turbines, and lithium-ion battery storage which is coupled to the utility grid. For modeling and simulation of the optimal system design of the residential load in Urir char, Hybrid Optimization Multiple Energy Resources (HOMER) pro was utilized. The load profile for the system was created employing fuzzy logic and random probability, as well as meteorological data for the chosen location. Several instances with reliability factors such as short-term and long-term interruptions are also taken into consideration in the design. Additionally, the paper discussed a comparison between the proposed system and other considered scenarios as well as the utility grid. The proposed system is a viable approach for providing cleaner energy for the selected area in regards to energy cost (0.035$/kWh), a renewable fraction (90 % ), emission reduction (78%), and reliability.

关键词： Renewable energy sources Costs Microgrids signal processing Stability analysis Planning Wind turbines

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Design and Implementation of IoT-Based Smart Energy Meter to Augment Residential Energy Consumption

Design and Implementation of IoT-Based Smart Energy Meter to...

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international conference on Robotics,Electrical and signal processing Techniques (ICREST)

作者： Md Abul Hayat Shahjee Midul Shahadat Hossain Pranta Al Shaharea Islam Biddut Sifatul Islam Siam Md. Rifat Hazari Mohammad Abdul Mannan Department of Electrical and Electronic Engineering American International University-Bangladesh Dhaka Bangladesh

There is a constant push for automation, portability, and remote control in the management systems of all organizations. A new IoT -based multifunctional smart energy meter is presented in this paper for automated metering and billing system. Arduino Nano with GSM Short Message Service (SMS) connection provides a meter reading system with predefined automatic functions followed by ESP-8266 WiFi Module to monitor energy parameters. Proteus 8.0 was used to model the project before the hardware implementation was built. With the GSM module and embedded controller, the proposed system can transmit data such as kWh consumption and generated bills over the GSM network, which can then be fed into existing energy management systems at power companies or organizations to provide services to customers without the need for human intervention. As a result, consumer energy analysis is made considerably simpler and more manageable. This device aids in the detection of power theft as well. As a result, this smart meter facilitates wireless connection and home automation utilizing IoT, which is a significant step towards a Digital Bangladesh. Moreover, a prepaid mode is incorporated as part of billing system.

关键词： Meters GSM Home automation signal processing Message services Smart meters Wireless fidelity

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Design and Implementation of Smart Drainage System for Bangladesh

Design and Implementation of Smart Drainage System for Bangl...

引用

international conference on Robotics,Electrical and signal processing Techniques (ICREST)

作者： Mohammad Shamiul Alam Sawnjida Sitara Afroza Sultana Irin Anika Tabasum Anu Abir Ahmed Md. Saniat Rahman Zishan Department of Electrical and Electronics Engineering American International Univerisity-Bangladesh (AIUB) Dhaka Bangladesh

As most of the areas in Bangladesh have adopted an underground drainage system, it is very important that this system work in a proper manner to keep the country clean, safe, and healthy. Failure to maintain regular monitoring of the drainage system results in the contamination of rainwater with drainage water, which spreads infectious diseases. This paper presents the implementation and design of a microcontroller-based drainage system for monitoring and maintaining the continuous movement of rainwater inside an underground drainage system remotely from a workstation. Using the Internet of Things (IoT), various parameters like water level, block detection, rainfall rate, etc. are monitored and stored on the cloud for analysis. The system also provides a forecast using Fisher's Rules. This enables the person in charge to take the necessary actions regarding the issue and send warning signals to the public.

关键词： Roads Urban areas Weather forecasting signal processing Solids Water pollution Software

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CNN-based image analysis for EEG signal characterization

CNN-based image analysis for EEG signal characterization

引用

3rd international conference on Biomedicine and Bioinformatics Engineering, ICBBE 2023

作者： Li, Yanqi Department of Architecture and Information Technology Faculty of Engineering University of Queensland Brisbane Australia

ISBN: (纸本)9781643684321

This article focuses on an attempt to classify and recognize the characterized images of EEG signals directly. For EEG signals, the recognition and judgment of different signals has been the key direction of research. CNN (Convolutional Neural Network) models are usually used for recognition of EEG raw signals about movement and Imagery dataset. However, the images of EEG raw signals are basically unreadable for researchers, so characterization is a common tool. However, direct recognition of the characterized images is a relatively empty area in the existing research because it requires much higher machine performance than the traditional raw signal recognition. However, feeding the extracted feature images into a CNN and training them can be an efficient and intuitive response to the potential of EEG for brain mapping. The main goal of this research is to examine the discriminative capabilities of traditional visual and image neural networks for pictures described by EEG data. This is not typical in contemporary brain-computer interface research. The direct recognition of the described photos uses a lot of GPU (graphics computing unit) resources, but for the characterized images are easier for people to read than the original images. This work indicates the viability of direct research on defined pictures and increases the application scenario of EEG signals. © 2023 IOS Press. All rights reserved.

关键词： Brain mapping

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A Comprehensive Study of Camouflaged Object Detection Using Deep Learning

A Comprehensive Study of Camouflaged Object Detection Using ...

引用

international conference on Robotics,Electrical and signal processing Techniques (ICREST)

作者： Khalak Bin Khair Saqib Jahir Mohammed Ibrahim Debajyoti Karmaker Computer Science & Engineering American International University Bangladesh(AIUB)

Various living organisms and objects around us often blend themselves with their environment and is thus invisible to the naked eye. Whether it is an organism like a pygmy seahorse, a warfare tank or a soldier, the Camouflage Object Detection Using Deep Learning overcomes these issues of objects hiding within the environment. In addition to object detection, we detect camouflage objects within an image using deep learning techniques. Deep learning is a subset of machine learning that is essentially a three-layer neural network. Over 6500 images that possess camouflage properties are gathered from various internet sources and divided into four categories to compare the result. Those images are labeled and then trained and tested using VGG16 architecture. The architecture is further customized using transfer learning. The purpose of this transfer of learning methodologies is to aid in the evolution of machine learning to the point where it is as efficient as human learning.

关键词： Deep learning Transfer learning Neural networks Object detection signal processing Organisms Robots

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Customer Adaptive Automated Trading System with Capital Risk Analysis using Machine Learning 3

Customer Adaptive Automated Trading System with Capital Risk...

引用

3rd international conference on signal processing and Communication (ICPSC)

作者： Agarwal, Harsh Kandoi, Aditi Ahir, Bhavya Dhage, Sudhir Sardar Patel Inst Technol Dept Comp Engn Mumbai 400058 Maharashtra India

ISBN: (纸本)9781665428644

Stock market plays a huge role in the economy of our country. Several attempts have been made to analyse and predict the stock market. While the existing systems try to exploit the patterns of stock prices using historical data, they do not take into the account the poor performance of the system. Moreover, there is no system which provides user specific trading strategies. The proposed solution explores filtration and different trading strategies using RoCE and Fuzzy Logic to solve the problem and predict the portfolio values. It also takes into consideration the sentiment aspect of trading using NLP and combines the two to efficiently to perform trading for even those users who have smattering knowledge about stock market thereby making it suitable for everyone.

关键词： Automated System Algorithmic Trading Price Prediction data Analysis

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