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The Art of YOLOv8 Algorithm in Cancer Diagnosis using Medical Imaging

The Art of YOLOv8 Algorithm in Cancer Diagnosis using Medica...

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IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)

作者： N. Palanivel Deivanai S Lakshmi Priya G Sindhuja B Shamrin Millet M Dept. of Computer Science & Engineering Manakula Vinayagar Institute of Technology Puducherry India Department of ECE Sri Krishna College of Engineering and Technology Coimbatore

Cancer continues to be a global health challenge, demanding innovative solutions to improve early detection and treatment outcomes. This research project harnesses the power of deep learning in the field of medical imaging to investigate the applicability of the YOLOv8 (You Only Look Once version 8) algorithm for diagnosing various cancer types, such as Acute Lymphoblastic Leukemia, Cervical, Lung, Colon, Oral, and Skin cancers. The YOLOv8 algorithm, renowned for its real-time object detection prowess, represents a promising candidate for automating the identification and classification of cancerous regions within medical images. This study encompasses a comprehensive methodology, starting with the collection and preprocessing of diverse and well-annotated medical image datasets. The YOLOv8 algorithm is then fine-tuned and trained on these datasets, capitalizing on its object detection capabilities to discern cancerous lesions. The model's performance undergoes a comprehensive evaluation using established metrics, guaranteeing its dependability and precision within a clinical setting. The findings of this study have the potential to offer insightful information on YOLOv8. By bridging the gap between cutting-edge deep learning technology and clinical practice, this research project seeks to advance the field of medical imaging and provide a foundation for more precise, efficient, and accessible cancer detection methods. Ultimately, the goal is to enhance the early diagnosis of cancer, offering new possibilities for timely intervention and improved patient outcomes.

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Energy-efficient Broadcast Trees for Decentralized Data Dissemination in Wireless Networks

Energy-efficient Broadcast Trees for Decentralized Data Diss...

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Conference on Local computer Networks (LCN)

作者： Artur Sterz Robin Klose Markus Sommer Jonas Höchst Jakob Link Bernd Simon Anja Klein Matthias Hollick Bernd Freisleben Dept. of Mathematics & Computer Science University of Marburg Germany Dept. of Computer Science Technical University of Darmstadt Germany Dept. of Electrical Engineering & Information Technology Technical University of Darmstadt Germany

We present a novel multi-hop data dissemination protocol for wireless networks that minimizes the total energy consumption across an entire network by minimizing the transmission power at each hop. It is based on a game-theoretic model, constructs a spanning tree topology in a decentralized manner, and is usable in practice. We evaluate the protocol via simulation and a pratical implementation on a testbed of 75 Raspberry Pis, demonstrating that a total energy reduction of up to 90% can be achieved compared to a simple broadcast protocol.

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A Survey on Anomaly Detection in IoT and Cloud Computing Security

A Survey on Anomaly Detection in IoT and Cloud Computing Sec...

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International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

作者： Gagan P Josy Elsa Varghese Seema G Aarella Dept. of CSE(Cyber Security) and CSE( AI and ML) Ramaiah Institute of Technology Bangalore India Dept. of Computer Science and Engineering University of North Texas Denton Texas USA

ISBN: (数字)9798350376425

ISBN: (纸本)9798350376432

Cybersecurity in the Internet of Things (IoT) is crucial for ensuring the safety of various applications. The advent of Artificial Intelligence (AI) has enabled innovative security solutions across multiple layers of the IoT ecosystem. As IoT rapidly integrates with edge computing to reduce latency compared to cloud computing, the cloud continues to offer high-speed computation, extensive data analytics, and enhanced security. This survey examines anomaly detection in Cloud-IoT environments, focusing on maintaining safety and functionality. We analyze current security threats, such as data breaches and unauthorized access, while also discussing the benefits and challenges of Cloud IoT, including scalability and privacy concerns. This study aims to explore the effectiveness of cloud-based IoT deployments by reviewing cutting-edge methodologies.

关键词： Internet of Things Anomaly detection Cloud computing Data models Security Computational modeling Analytical models Image edge detection Deep learning computer architecture

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Electromagnetic Near-Field Scanning with a Spatially Sparse Sampling Strategy Utilizing Kriging-DMD

Electromagnetic Near-Field Scanning with a Spatially Sparse ...

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IEEE Workshop on Signal Propagation on Interconnects (SPI)

作者： Yanming Zhang Steven Gao Lijun Jiang Dept. of Electronic Engineering Chinese University of Hong Kong Hong Kong Dept. of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO USA

ISBN: (数字)9798350382938

ISBN: (纸本)9798350382945

This paper proposes a hybrid method for time-resolved electromagnetic near-field scanning, merging model-based (Gaussian processes regression model, a.k.a. Kriging method) and data-driven (dynamic mode decomposition) techniques. Specifically, Latin hypercube sampling enables spatially sparse measurements, followed by dynamic mode decomposition to analyze resulting sparse spatial-temporal data, extracting frequency information and sparse dynamic modes. The Kriging method is then employed for full-state reconstruction. The proposed approach is evaluated using crossed dipole antennas. Results indicate that, even with a spatial subsampling factor of 130, achieving a fully reconstructed field distribution suitable for engineering applications with frequency information extraction is feasible. This hybrid framework presents a promising avenue to enhance efficiency in electromagnetic near-field measurements, potentially finding applications across diverse electromagnetic measurement scenarios.

关键词： Antenna measurements Electromagnetic measurements Dipole antennas Merging Gaussian processes Information retrieval Hypercubes

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Integrated Modeling of Wireless System Performance under Beaulieu-Xie Fading and κ-μ Co-Channel Interference: A Multi-Dimensional Exploration

Integrated Modeling of Wireless System Performance under Bea...

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International Symposium on Wireless Personal Multimedia Communications (WPMC)

作者： Deepak Upadhyay Kunj Bihari Sharma Rashmi Sharma Nookala Venu Dept. of Computer Science and Engineering Graphic Era Hill University Dehradun India Dept. of Computer Science and Engineering Graphic Era deemed to be University Dehradun India Department of CSE Symbiosis Institute of Technology Nagpur Campus Symbiosis International (Deemed University) Pune India Centre for Internet of Things Madhav Institute of Technology & Science Deemed University Gwalior India

ISBN: (数字)9798350392319

ISBN: (纸本)9798350356137

This paper proposes simulation and analysis to discuss how the fading affects the wireless signal waves on different fading levels. Four types of fading: (i) no fading, (ii) a low level of fading, (iii) moderate level of fading and (iv), high level of fading was considered for simulating the signal amplitude over time. Selected fading levels were ‘added’ to model real world wireless scenarios in which both environmental and interference conditions are at play. The results indicated that in the absence of fading, the amplitude of the signal wave was continuous and not changed significantly; however, from low to severe fading, there could be directly proportional soaring fluctuations in its proper amplitude corresponding to lose of signal strength. Together, these findings underscore the importance of adaptive signal processing techniques and robust modulation strategies in suppressing the degradative effects of fading against the desirable characteristics of proper signal integrity and reliable performance. The findings highlight one reality in communications: understanding fading is critical for designing ultrareliable wireless systems that perform consistently across a variety of operational settings. The knowledge extracted based on this study would further add to novel way of designing robust strategies for Signal resilience and Communication reliability emerged in future wireless networks.

关键词： Fading channels Wireless communication Fluctuations Wireless networks Modulation Signal processing algorithms Reliability engineering Adaptive signal processing Robustness Signal integrity

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The Role of AI in Optimizing Healthcare Appointment Scheduling

The Role of AI in Optimizing Healthcare Appointment Scheduli...

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Disruptive Technologies (ICDT), International Conference on

作者： Bhupendra Kumar MD. IQBAL Reeta Parmer Puneet Garg Sunita Rani Atul Agrawal Department of Computer Science & Engineering ITS Engineering College Greater Noida India Department of Computer Science & Engineering Quantum University Roorkee India dept. name of organization St. Andrews Institute of Technology and Management Gurugram Delhi NCR India Computer Science and Engineering (AI) KIET Group of Institutions Delhi NCR Ghaziabad India Golgoti University Greater Noida India Computer Science and Engineering ITS Engineering College (AKTU) Greater Noida India

ISBN: (数字)9798331519582

ISBN: (纸本)9798331519599

AI is the most interesting area of healthcare, which is currently making its way into the medical field. Artificial Intelligence has become a game changer, in the healthcare industry bringing forth solutions to problems. A particular area of focus for AI advancements in years has been appointment scheduling with the aim of improving efficiency and accessibility for patients. To overcome these challenges AI technologies have been utilized to develop scheduling systems that utilize data-driven insights and machine learning algorithms. This paper is to investigate appointment scheduling systems in the healthcare sector. The healthcare sector is a major part of the economy. Through surveys, the appointment scheduling system can improve its efficiency. Artificial Intelligence proposes methods for advancing appointment scheduling, which helps control the scheduling window. It can reduce patient no-shows, manage long waitlists, take rapid action over medical urgency, and enhance the department's use of resources for outpatients. Further, the paper examines the problem of appointment management in the healthcare sector considering the various outcoming problems. This paper overlooks the different components of Artificial Intelligence that are applied to the appointment system. We also observe the challenges in the system and the open issues. The objective is to improve the appointment system in the healthcare sector and regulate it with the advancement of Artificial Intelligence.

关键词： Surveys Privacy Job shop scheduling Machine learning algorithms Natural languages Medical treatment Medical services Planning Teamwork Artificial intelligence

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Comparative Study of Motion Correction Algorithms for Contrast-Enhanced Ultrasound Imaging 21

Comparative Study of Motion Correction Algorithms for Contra...

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21st IEEE India Council International Conference, INDICON 2024

作者： Shubham Ghosh, Debabrata Chowdhury, Kuntal Mathur, Manoj Thapar Institute of Engineering & Technology Dept. of Electronics and Communication Engineering Patiala India Thapar Institute of Engineering & Technology Department of Computer Science & Engineering Patiala India Government. Medical College Department of Radiodiagnosis Patiala India

ISBN: (纸本)9798350391282

Due to its speed, safety, and affordability, ultrasound imaging is preferred in medical diagnosis;nonetheless, speckle noise and limited scan lines cause detail loss. Contrast-Enhanced Ultrasound (CEUS) enhances tissue perfusion and tumor detection using microbubbles but is prone to motion artifacts, particularly in dynamic settings like Dynamic Contrast-Enhanced Ultrasound (DCE-US), where patient or probe movement degrades image quality. Motion artifacts in traditional DCE-US are usually corrected by removing the affected frames, which leads to a loss of useful data. To maintain image integrity and improve clinical analysis, recent advances have concentrated on motion correction algorithms. Using quantitative metrics like Root Mean Square Error (RMSE), Correlation Coefficient (CC), and qualitative assessment through visual inspection of Maximum Intensity Projection (MIP), this paper assesses three such algorithms: Block Matching Algorithm, Sub Pixel Registration, and 2-Tier image registration. The objective is to determine the most efficient technique for reducing motion artifacts and enhancing both qualitative and quantitative analyses in medical imaging. © 2024 IEEE.

关键词： Ultrasonography

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DigiPramaan: Blockchain Based Certificate Management System

DigiPramaan: Blockchain Based Certificate Management System

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International Conference on Computing Communication Control and Automation (ICCUBEA)

作者： Prathamesh Swami Kapil Vhatkar Yash Ambekar Kartikey Singh Yashovardhan Kaware Dept. of Computer Engineering Dr. D. Y. Patil Institute of Technology Pune India

ISBN: (数字)9798350391770

ISBN: (纸本)9798350391787

With more people taking online courses and earning certifications, there are great new opportunities to improve skills. But, this digital trend has also led to a problem with fake certificates. To address this problem, we propose a robust certificate management system utilizing blockchain technology and smart contracts. Our system comprises three key components: certificate creation, authenticity verification, and a user-friendly digital storage solution. Blockchain technology is at the core of our system, ensuring that each certificate is immutable and trustworthy. We utilize cryptographic hashes as unique identifiers for each certificate, which detect any tampering by resulting in a different hash. Additionally, our system offers secure digital storage based on cloud technology, allowing users to efficiently manage and access their certificates. We also emphasize features for certificate revocation and updates, enhancing the system’s security and adaptability. In conclusion, our blockchain based system offers a comprehensive and secure solution to the issue of fake certificates in the digital era.

关键词： Automation Smart contracts Authentication Access protocols Market research Blockchains Reliability Digital storage Certification

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Crack Catcher AI - Enabling Smart Fracture Mechanics Approach for Damage Control in Thin Silicon Wafers for 3D Semiconductor Integrated Devices/Packages

Crack Catcher AI - Enabling Smart Fracture Mechanics Approac...

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2025 IEEE International Reliability Physics Symposium, IRPS 2025

作者： Preston, Gabriel Gonzolez, Greer Karnyoto, Andrea S. Mozar, Fitya S. Henry, Matthew M. Isnan, Mahmud Nugroho, Kuncahyo S. Candra, Henry Doris, Muhamad Putri, Dianing N. N. Sari, Tyas K Pardamean, Bens Djuana, Endang Speaks, Derrric Budiman, Arief S. Klamath FallsOR97601 United States Oregon Institute of Technology Klamath FallsOR97601 United States Bina Nusantara University Jakarta11480 Indonesia Universitas Trisakti Jakarta11440 Indonesia Department of Electrical Engineering Faculty of Industrial Technology Universitas Trisakti Jakarta11440 Indonesia Industrial Eng. Dept. Bina Nusantara University Jakarta11480 Indonesia Computer Sci. Dept. Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9798331504779

The importance of silicon cannot be undermined - in photovoltaics (PV) as well as in semiconductor industries. However, silicon is very brittle. Silicon cells/wafers crack easily during manufacturing assembly and/or during device operations. Crack Catcher AI uses novel smart fracture mechanics approach with Artificial Intelligence (AI) methodologies to predict and control crack/damage evolution in thin silicon cells/wafers. This is critical as semiconductor 3D integration technology calls for wafer-to-wafer bonding with utmost alignment accuracy and yield/reliability. © 2025 IEEE.

关键词： Silicon wafers

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Quantitative Trends Analysis on Russian Literature Research in Korean Academia: Insights from KCI Data

Quantitative Trends Analysis on Russian Literature Research ...

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International Conference on Platform technology and Service (PlatCon)

作者： Ten Alexander Iosifovich Sang-Soo Yeo Young-Ae Jung Dept. of Computer Science Sun Moon University Asan South Korea Dept. of Computer Engineering Mokwon University Daejeon South Kora Dept. of AI Software Technology Sun Moon University Asan South Korea

ISBN: (数字)9798350367874

ISBN: (纸本)9798350367881

This paper presents a quantitative analysis of trends in Russian literature and Korean-Russian translated literature within Korean academia from 1996 to 2024. By analyzing frequency themes and contexts, the study explores evolving research trends, revealing how sociocultural, political, and artistic exchanges between Korea and Russia have influenced each other. Future research using text mining promises to uncover more specific patterns, offering deeper insights into literary and cultural exchanges. This study contributes to understanding the role of literature in expressing and understanding sociopolitical and cultural values in both countries.

关键词： Text mining Translation Statistical analysis Data visualization Curriculum development Market research Cultural differences Indexes

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