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Application of 3D Printing and Design in Healthcare: A Focus on Undergraduate Research to Attract Students to Bioengineering and Related Disciplines 54

Application of 3D Printing and Design in Healthcare: A Focus...

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54th IEEE Frontiers in Education Conference, FIE 2024

作者： Zelada-Quiroz, Cindy M. Reyes-Santiago, Brian L. Ortiz-Rivera, Eduardo I. University of Puerto Rico at Mayagüez Bio-Engineering Graduate Program Mayagüez Puerto Rico University of Puerto Rico at Mayagüez Department of Computer Science and Engineering Mayagüez Puerto Rico University of Puerto Rico at Mayagüez Department of Electrical and Computer Engineering Mayagüez Puerto Rico

ISBN: (纸本)9798350351507

This research-to-practice paper describes developing and analyzing state-of-the-art smart boots created by combining CAD technology and advanced 3D printing techniques to attract students in bio-engineering and related fields. The primary objective of this innovative immobilization boot is to expedite fracture recovery phases through an ergonomic design to ensure optimal patient comfort during its use. Technological solutions are crucial in aiding the rehabilitation process for fractures caused by falls, heavy lifting, or rotational trauma. However, cost and comfort-related issues persist, underscoring the need for alternative approaches. This research addresses these challenges and delves into the broader implications of fracture treatment, catalyzing future projects and investigations in bioengineering. Additionally, this study serves as an educational tool that sparks the interest of high school and engineering students, promoting multidisciplinary collaboration in innovation. By involving students in specialized courses covering 3D design, human bone anatomy, biology, and materials science, this initiative empowers them to deepen their knowledge and develop new technologies to address bone injury problems. Material analyses include evaluating the type of material depending on the fracture site, such as PLA for printing and cotton and silicone gel for the midsection between the splint and the body. This research aims to advance our understanding of the type of fracture, the methods associated with their treatment, and tissue repair processes during bone callus formation. To summarize, this multidisciplinary approach drives advancements in bio-engineering and related fields, aiming to enhance patient outcomes and inspire students to pursue further research in bio-engineering and related fields. As part of this endeavor, a list of university-level courses based on the experience of the University of Puerto Rico at Mayaguez (UPRM), such as biology, bio-materials, 3D

关键词： Students

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Detection of pneumonia progression in lungs of individuals affected with covid 19 severely using deep learning techniques 3

Detection of pneumonia progression in lungs of individuals a...

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3rd International Conference for Emerging Technology, INCET 2022

作者： Gadipudi, Praneeth Teja, Palachuri Sai Yelamancheli, Chandana Sowmya. Thaniserikaran, Adith Mohiuddin, Rayyan Joy, Ajin Srm University Department of Computer Science and Engineering Andhra Pradesh Amaravati India Srm Department of Computer Science and Engineering Institute of Science and Technology Tamil Nadu Kattankulathur India Icfai University Department of Computer Science and Engineering Hyderabad India National Institute of Technology Department of Computer Science and Engineering Telangana Warangal India National Institute of Technology Department of Electrical Engineering Telangana Warangal India JSPMs' Rajarshi Shahu College of Engineering Department of Electronics and Telecommunication Engineering Maharashtra Pune India

ISBN: (纸本)9781665494991

The coronavirus sickness (COVID-19) is a worldwide pandemic that was detected in December 2019 by a Chinese physician in Wuhan, Hubei Province, mainland China. There is presently no licensed human vaccine to combat it. When individuals are close together, COVID-19 spreads more fast. As a consequence, travel constraints are in place to minimize the disease from spreading, and regular Washing the hands is encouraged so that the infections that occur due to the virus. Other indications and symptoms include chest discomfort, sputum production, and a sore throat. COVID19 could lead to a very dangerous disease which is pneumonia which occurs due to the virus. When employing CT scans or Xrays to identify the symptoms that are occuring due to the cause of covid-19 in the last region of the lungs then the accuracy is better than when utilizing RT-PCR. But as there are very less radiologists as compared to the new residents or the people that have come and aslo there has been seen many re examinations occurring of these patients. To solve this kind of the issues or problems that is limiting the CT scans and the x-rays the speed of this procedure must be boosted. This may be done by adding artificial intelligence (AI) approaches into contemporary diagnostic systems. The main motive of the paper is to provide the best accuracy to detect the disease using CNN along with a comparison with the transfer learning approach. © 2022 IEEE.

关键词： computerized tomography

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Polygraph and audio synchronization applied to apnea event analysis based on non-negative matrix factorization

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EURASIP Journal on Audio, Speech, and Music Processing 2025年第1期2025卷 1-19页

作者： Gonzalez-Martinez, Francisco David De La Torre-Cruz, Juan Carabias-Orti, Julio Jose Canadas-Quesada, Francisco Jesus Salvador-Navarro, Alejandro Antonio Ranilla, Jose Laarbi, Lyam Lamrini-H. Departament of Telecommunication Engineering University of Jaen Linares Spain Department of Computer Science University of Oviedo Gijon Spain Pulmonology Department University Hospital of Jaen Jaen Spain

Obstructive sleep apnea (OSA) is a chronic respiratory disorder that is frequently underdiagnosed. The primary clinical methods for OSA detection are polysomnography (PSG) and polygraphy (PG). While these tests provide an accurate assessment of the patient’s condition, they remain impractical for large-scale population screening. Consequently, considerable research has been dedicated to developing audio-based OSA assessment techniques based on data from synchronized audio and PSG/PG recordings. Given that most PSG/PG equipment used in sleep centers lacks built-in support for synchronizing with audio recordings, this works presents a novel method for synchronizing audio with PG signals to enhance audio-based analysis of OSA. The proposed method introduces an iterative time-alignment algorithm based on the cross-correlation between an estimated respiratory sound signal and the nasal flow signal from PG. To estimate the respiratory sound from the captured sound signal, constrained non-negative matrix factorization (NMF) is applied using a combination of orthogonality and sparsity constraints to identify the component that best models the respiratory pattern of each analyzed audio segment. The synchronization performance of the proposed method was tested on a newly developed dataset comprising full-night measurements from 32 subjects, achieving a mean absolute error of less than one second. Finally, the developed dataset demonstrated its validity for OSA severity assessment by providing comparable results to those obtained from other datasets when evaluated using a state-of-the-art method.

关键词： Obstructive sleep apnea (OSA) Time-alignment Non-negative matrix factorization (NMF) Respiratory sounds Apnea-hypopnea index (AHI)

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Military Vehicle Object Detection Based on Feature Representation and Refined Localization Using Inception Recurrent Convolutional Neural Network 2

Military Vehicle Object Detection Based on Feature Represent...

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2nd International Conference on Distributed Computing and Optimization Techniques, ICDCOT 2024

作者： Almusawi, Muntather Yadav, S. G. Shivaprasad Rahim, Abdul Aluvala, Srinivas Ramachandra, A.C. The Islamic University Najaf Iraq Electronics and Telecommunication Engineering Ramaiah Institute of Technology Bangalore India Electronics and Communication Engineering Department Telangana Hyderabad India School of Computer Science and Artificial Intelligence Sr University Warangal India Nitte Meenakshi Institute of Technology Department of Ece Bengaluru India

ISBN: (纸本)9798350382952

Advanced reconnaissance technologies for military vehicle components form basis for weapons and equipment reconnaissance and tracking operations in complex environments, which is crucial to allow intelligent warfare using information. Addressing limitations of conventional detection algorithms in this domain, a novel approach termed as Military Vehicle Object Detection Method based on Inception Recurrent Convolutional Neural Network (MVODM-IRCNN) and Hierarchical Feature Representation is proposed for detecting military vehicle object. first is a comprehensive data set specially designed for military vehicles. Then it is two system improvements: hierarchical feature representation and state-of-the-art localization, using Inception Recurrent Convolutional Neural Network (IRCNN), aimed at improving detection performance. Hierarchical feature representation techniques make it easier to find good feature representation levels for different object shapes, improving accuracy of these techniques boxes. combination of materials provides a significant gain in detector performance. Finally, an exploratory study conducted on own dataset shows that MVODM-IRCNN has exceptional recognition capabilities, which proves its usefulness in military vehicle recognition applications. © 2024 IEEE.

关键词： Object detection

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A Novel Blockchain-Based Strategy for Energy Conservation in Cognitive Wireless Sensor Networks 4

A Novel Blockchain-Based Strategy for Energy Conservation in...

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4th International Conference on Blockchain Technology and Information Security, ICBCTIS 2024

作者： Sharma, Khemraj Goyal, Rohit Bhagat, Sukesh Kumar Agarwal, Sheenu Bisht, Girish Singh Hussien, Mohemmed Nanhua University Department of Business Administration Doctoral Program in Management Sciences Dalin62248 Taiwan School of Engineering and Computing Dev Bhoomi Uttarakhand University Dehradun India Uttaranchal University Department of Computer Science & Engineering Dehradun India Uttarakhand Technical University Department of Electronics and Communication Engineering Dehradun India Tula's Institute Dehradun India Department of Computer Science and Engineering Dehradun248001 India The Islamic University Najaf Iraq

ISBN: (纸本)9798331528324

Internet of Things (IoT) industrial applications have increased in internet-connected devices. As a result, accessibility, scalability, connectivity, and adaptability have become major challenges. It is possible to create connections between loT devices over the wireless medium, but efficiently utilizing scarce spectrum is the biggest concern. The paper proposes a novel method for selecting sensing nodes with the goal of reducing energy usage and increasing sensing efficiency. In order to ensure that node trust values conform to each other without any ambiguity, cryptography encrypts all information that relates to a node in a central node (CN). Nodes participating in CSS are selected based on their performance. Based on a comparison of various algorithms using varying numbers of nodes, the proposed algorithm achieves a 10% sensing efficiency. © 2024 IEEE.

关键词： Blockchain Network Network Communication security Wireless Sensor

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An Enhanced Routing Protocol Design to Perform Cost Efficient Data Communication over Wireless Sensor Networks 3

An Enhanced Routing Protocol Design to Perform Cost Efficien...

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3rd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Jadhav, Dattatraya Arun Suneel, Sajja Begum, M. Amina Ghogare, Meghana Harsh Murri, Madhan Sekhar Vadar, Parashuram Shankar Keystone School of Engineering Electronic and Telecommunication Department pune India Telangana Hyderabad500043 India Oxford College of Engineering Department of Ece Tamilnadu Venmani India Parul University ByteXL-Department of Computer Science and Engineering Vadodara India Department of Management Studies AP India Shivaji University Yashwantrao Chavan School of Rural Development Maharashtra Kolhapur India

ISBN: (纸本)9798350375190

This research introduces a groundbreaking approach to address the challenges of cost-efficient data communication in Wireless Sensor Networks (WSNs) through the development of a novel routing protocol named Cost-Efficient Enhanced Routing Protocol (CEERP). WSNs, characterized by resource-constrained sensor nodes and dynamic environmental conditions, necessitate innovative routing strategies to optimize energy consumption and enhance overall network performance. CEERP leverages a sophisticated methodology that integrates Energy Consumption Modeling, Adaptive Routing Decisions, alongside Optimization and Fine-Tuning. The Energy Consumption Modeling method systematically analyzes various factors influencing energy dynamics in sensor nodes, facilitating the creation of accurate mathematical models. These models inform CEERP's routing algorithm, enabling intelligent decisions based on predicted energy consumption patterns. The protocol adapts dynamically to real-time variations in network conditions, ensuring responsiveness to changing environmental factors. Implementation and Simulation validate CEERP's performance in diverse scenarios, while Optimization and Fine-Tuning finetune parameters for optimal efficiency. Security and reliability measures are integrated to safeguard data integrity. The research concludes with a comprehensive evaluation of CEERP's effectiveness, positioning it as a promising solution for achieving cost-efficient and reliable data communication in WSNs. The proposed methodology and CEERP contribute to the advancement of routing protocols for WSNs, offering a holistic and adaptive approach to address the unique challenges posed by resource-constrained environments. © 2024 IEEE.

关键词： Routing protocols

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Meal Image Recognition and Healthy Meal Combination Recommendation System Integrated with Generative Artificial Intelligence 6

Meal Image Recognition and Healthy Meal Combination Recommen...

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6th IEEE Eurasia Conference on Biomedical engineering, Healthcare and Sustainability, ECBIOS 2024

作者： Chang, Chin-Chih Wei, Chi-Hung Hsiao, Sean Yang, Chyuan-Huei Thomas Chung Hua University Department of Computer Science and Information Engineering Hsinchu Taiwan Chung Hua University Ph.D. Program in Engineering Science Hsinchu Taiwan Chung Hua University Program in Applied Foreign Language and Smart Commerce Hsinchu Taiwan School of Information Engineering Shandong Vocational and Technical University of International Studies Shandong China

ISBN: (纸本)9798350396133

People increasingly prioritize a balanced diet to enhance well-being, yet making informed dietary choices remains challenging amidst the abundance of options. To address this, we developed a meal image recognition and healthy meal combination recommender system, integrating generative artificial intelligence (AI). Convolutional neural networks were used for precise meal image recognition to identify diverse food items. The generative AI-augmented recommendation engine offers personalized meal suggestions aligned with nutritional goals and dietary preferences, utilizing a nutrition knowledge base to ensure overall well-being. The system's feasibility was validated, illustrating its excellence in meal recognition accuracy, recommendation diversity, and user engagement. By integrating generative AI, the system shows its potential to enhance dietary recommendations and public health. © 2024 IEEE.

关键词： Generative adversarial networks

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Prediction of Cardiovascular Disease Risk in the General Population: A GSA-ELM Approach 1

Prediction of Cardiovascular Disease Risk in the General Pop...

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1st IEEE International Conference on Electronics, Computing, Communication and Control Technology, ICECCC 2024

作者： Lohbare, Sonali Pakhmode Noor Alleema, N. Praveena, S. Patil, Harshal Rajalakshmi, S. Lakineni, Prasanna Kumar Raisoni University Amravati VPPCOE & VA Department of Electronics and Telecommunication Soin Mumbai India Thandalam Department of CSE Chennai India Mahatma Gandhi Institute of Technology Gandipet Department of ECE Telangana Hyderabad India Department of CSE Maharashtra Pune India RMK College of Engineering and Technology Department of Electronics and Communication Engineering Chennai India Sri Venkateswara College of Engineering Department of Computer Science & Engineering Tirupathi India

ISBN: (纸本)9798350371802

Medical treatment is a need since it ensures our continued existence as a species. Conditions affecting the heart and blood arteries are collectively known as cardiovascular disease. Decisions regarding the appropriate medicines for people at high risk for cardiovascular disease were informed by early methods of illness prediction. Machine learning algorithms are crucial for creating reliable forecasts of cardiac problems because of the abundance of available health care data. The proposed method is based on three primary phases: preprocessing, feature extraction, and model training. To lessen the impact of distracting noise, HD statistics use filtering and de-noising during the preprocessing phase. In order to extract features, the gray-level Co-Occurrence Matrix is employed. Next, GSA-ELM models are trained based on the retrieved characteristics. Compared to GSA and ELM, the two most popular alternatives, the suggested technique is better. They were able to reach a maximum accuracy of 95.74% by implementing the suggested technique. © 2024 IEEE.

关键词： Forecasting

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A Scientometric Review and Research Trends of Internet of Things in Application of Smart City 11

A Scientometric Review and Research Trends of Internet of Th...

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11th International Conference on ICT for Smart Society, ICISS 2024

作者： Maulana, Fairuz Iqbal Prasetyo Adi, Puput Dani Pramono, Andi Rahayu, Anita Persada, Satria Fadil Nadlifatin, Reny School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Research Center for Telecommunication National Research and Innovation Agency Bandung Indonesia School of Design Bina Nusantara University Interior Design Department Jakarta11480 Indonesia Binus Business School Undergraduate Program Bina Nusantara University Entrepreneurship Department Jakarta Indonesia Institut Teknologi Sepuluh Nopember Department of Information System Surabaya Indonesia

ISBN: (纸本)9798350389654

The Internet of Things (IoT) has revolutionized the concept of Smart Cities by enabling the seamless integration of various technologies and devices to enhance urban living. This abstract presents a comprehensive overview of the research trends and advancements in IoT applications within Smart Cities from 2019 to 2023. By conducting a scientometric review and bibliometric analysis using R studio and VOSviewer software, this study aims to identify key focus areas, challenges, and opportunities in the implementation of IoT technologies in urban environments. Data selection from the Scopus database yielded a total of 3849 documents from 1515 sources. The most cited article from 2021 is 166 citations. Average citations per doc is 18.56. China, India, and Korea appear to dominate in terms of the number of published documents. Future research directions include exploring innovative solutions leveraging technologies like blockchain, edge computing, and artificial intelligence to improve the efficiency, sustainability, and resilience of Smart City initiatives. By synthesizing insights from existing literature and exploring emerging trends, this study contributes to the advancement of Smart Cities and the development of a more connected and intelligent urban future. © 2024 IEEE.

关键词： Sustainable city

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Morse Code Based Two-Way Communication Device for Visually Impaired and Mute

Morse Code Based Two-Way Communication Device for Visually I...

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Device Intelligence, Computing and Communication Technologies, (DICCT), International Conference on

作者： Abha Marathe Snehal Bawanthade Rohit Bele Nidhi Bhagwat Avinash Bhurke Department of Electronics and Telecommunication Engineering Vishwakarma Institute of Technology Pune India Department of Computer Science Engineering Vishwakarma Institute of Technology Pune India

ISBN: (数字)9798331543358

ISBN: (纸本)9798331543365

People with disabilities like visual and speech impairments face significant challenges in interacting and communicating with others because conventional tools like smartphones are predominantly visual and verbal based. Consequently, such individuals depend on others even to convey simple messages. These problems restrict their ability to express themselves freely. Moreover, existing assistive technologies are complex and expensive making them impractical choice for widespread use. This project presents an innovative solution to overcome these obstacles: a Morse-code-based device that operates on a single-button interface thus making it extremely useful for people who can't see. This IOT-based device translates Morse code signals into text which is further displayed on mobile devices. Additionally, the message logs are preserved on cloud storage thus ensuring convenience and accessibility to the users. The morse code inputs are captured by the push button presses and then converted to readable text with the help of the microcontroller ESP8266, which further gives visual outputs through LCD and audio outputs through the buzzer. The device also supports two-way communication, that is two similar devices can send and receive messages from each other easily, thus even if two disabled people have to communicate with each other, they can do so without any difficulty. This function enables interaction between individuals with similar kinds of disabilities and fosters inclusivity and mutual understanding. It aims to promote independence and social engagement. The service is highly practical, cost-effective, and most importantly, easy to use.

关键词： Visualization Presses Codes Translation Speech coding Microcontrollers Visual impairment Assistive technologies People with disabilities Smart phones

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