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Automated Leukemia Diagnosis from Microscopic Blood Smear Images Using Adapted Inception V3

Automated Leukemia Diagnosis from Microscopic Blood Smear Im...

引用

2024 International Conference on Big data Analytics in Bioinformatics, DABCon 2024

作者： Pujitha, M Vani Srikantam, Srinija Sahithi, Ch Timmasarti, Akhila Velagapudi Ramakrishna Siddhartha Engineering College Dept. of Computer Science and Engineering Vijayawada India

ISBN: (纸本)9798350378047

Leukemia, a cancer characterized by the rapid overproduction of abnormal blood cells, presents notable diagnostic and treatment challenges. Identifying leukemia subtypes promptly and accurately is vital for devising effective treatments and improving patient outcomes. This study proposes an advanced Inception V3 model optimized for the automatic identification of leukemia from microscopic images of blood smears. By integrating cutting-edge deep learning methods and a customized model architecture, this system differentiates between Acute Lymphoblastic Leukemia (ALL), Acute Myeloid Leukemia (AML), Chronic Lymphocytic Leukemia (CLL), Chronic Myeloid Leukemia (CML), and healthy samples. The model benefits from preprocessing techniques like image resizing, normalization, and augmentation to enhance its performance. Through transfer learning, the Inception V3 model is fine-tuned on a rich dataset covering various leukemia subtypes. Experimental results demonstrate the model's high effectiveness, achieving 100% accuracy during training and 99.72% accuracy in testing, proving the system's reliability for automated leukemia detection. © 2024 IEEE.

关键词： Lung cancer

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Real-Time Flow Scheduling in Industrial 5G New Radio 44

Real-Time Flow Scheduling in Industrial 5G New Radio

引用

44th IEEE Real-Time Systems Symposium, RTSS 2023

作者： Zhang, Tianyu Wang, Jiachen Hu, Xiaobo Sharon Han, Song University of Connecticut Dept. of Computer Science and Engineering United States University of Notre Dame Dept. of Computer Science and Engineering United States

ISBN: (纸本)9798350328578

Among the many industrial wireless solution candidates, 5G New Radio (NR) has drawn significant attention in recent years due to its capabilities to support ultra-high-speed communication, ultra-low latency, and massive connectivity. Despite its great potential, 5G NR also brings significant complexity in scheduling industrial data flows to meet their hard real-time requirements. In this paper, we first leverage a real-world 5G RAN testbed to benchmark the downlink throughput and explore the impact of modulation and coding scheme (MCS) selection on the network performance. We then formulate a real-time flow scheduling problem in industrial 5G NR, which features per-flow real-time schedulability guarantees through time-frequency-space resource allocation. We propose a novel two-phase scheduling framework, named 5G-TPS, to construct the schedule that meets the deadlines of all the flows. To adapt to dynamic channel conditions, 5G-TPS enables online schedule adjustment for affected flows to meet their timing requirements. To evaluate the performance of 5G-TPS, we present a case study of a motion control panel use case and perform extensive experiments. The results show that 5G-TPS can achieve schedulability ratios comparable to the Satisfiability Modulo Theory (SMT)-based exact solution and outperform many other state-of-the-art scheduling approaches, including the built-in 5G NR schedulers. © 2023 IEEE.

关键词： Benchmarking

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A computer science Perspective on Digital Sustainability: A Thematic Literature Review 22

A Computer Science Perspective on Digital Sustainability: A ...

引用

22nd IEEE Consumer Communications and Networking Conference, CCNC 2025

作者： Delnevo, Giovanni Olaiya, Kelvin Salomoni, Paola University of Bologna Dept. of Computer Science and Engineering Bologna Italy

ISBN: (纸本)9798331508050

This paper explores the evolving concept of digital sustainability, emphasizing its growing importance as digital technologies become essential to addressing global sustainability challenges. Through a thematic literature review focused on computer science, we analyze papers from Scopus-indexed journals to identify key themes in the discourse on digital sustainability. Additionally, we map the identified topics to the traditional three-pillar model of sustainable development, noting areas of alignment and divergence. The study offers insights into how digital sustainability is framed within the computer science literature and its implications for future research. © 2025 IEEE.

关键词： Green development

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Advancements in User Security: Enhancing Usability with Graphical Password Authentication 2

Advancements in User Security: Enhancing Usability with Grap...

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2nd International Conference on Intelligent data Communication Technologies and Internet of Things, IDCIoT 2024

作者： Harisha Naik, Sandhya Ramesh Vasudeva, Shettigar Sarvani Shrilakshmi, K. Kothwal, Vaishnavi Sahyadri College of Engineering & Management Dept. of Computer Science & Engineering Mangalore Karnataka India

ISBN: (纸本)9798350327533

Text-based password authentication is a common method used to verify the identity of users who are trying to access a secure system or service. In order to use this authentication method, the user must input a password or other secret phrase that is then compared to a server-side copy of the same password. Access is given if the password typed matches the one saved. Graphical password authentication is a type of user authentication that involves using images or visual elements instead of alphanumeric characters to verify the identity of the user. Unlike traditional text-based passwords, graphical passwords offer an intuitive and user-friendly way of authentication, as they rely on the user's ability to remember pictures, shapes, and patterns. This technology has been developed to address the limitations of traditional text-based passwords, such as the difficulty of creating and remembering complex passwords, and the vulnerability to brute-force attacks. Compared to conventional text-based passwords, graphical password authentication has a number of benefits, including better usability and higher security. © 2024 IEEE.

关键词： Authentication graphical passwords security

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IoT-Enhanced Smart Bulletin Board: A Multi-Functional Connectivity Hub 2

IoT-Enhanced Smart Bulletin Board: A Multi-Functional Connec...

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2nd International Conference on Intelligent data Communication Technologies and Internet of Things, IDCIoT 2024

作者： Gundavarapu, Mallikarjuna Rao Swapna, Veerlapalii Reddy, Enugu Sriamsh Kumar, Pindi Praveen Prathapani, Abhinay Shivaji, Kothapally Gokaraju Rangaraju Institute of Engineering and Technology Dept. of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350327533

The problem with traditional notice boards is their static nature, leading to outdated information and manual effort to update. An IoT-based smart notice board solves this by providing real-time updates but requires addressing challenges such as connectivity, power management, compatibility, user interface, security, and maintenance. Addressing these challenges ensures an effective and user-friendly smart notice board. The proposed model involves using an LED dot matrix, ESP32, Kodular app, Firebase Cloud and DS3231 module. The app sends messages to the Firebase then it passes the message to ESP32, which displays message on the LED dot matrix, We use Firebase cloud which provides infinite range. Firebase provides a NoSQL database that allows developers to store and synchronize data in real-time. It is suitable for applications that require real-time updates, such as chat apps, collaborative tools, and live dashboards. The DS3231 module shows real-time information. This study implements a feature that allows the user to retrieve the current time and temperature by pressing a button in the Kodular app. When the button is pressed, a command is sent to the ESP32, which retrieves the relevant data from the DS3231 module and sends it to display. This study creates a buffer to store messages, accessible by indexes, allowing easy retrieval. The proposed system provides a comprehensive solution for displaying messages, real-time data, and efficient message storage. QR codes are also provided to scan. © 2024 IEEE.

关键词： database Dot Matrix DS3231 ESP32 Firebase cloud IoT Kodular app LED Module NoSQL QR code Real-Time Updates

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Navigating the Landscape of Intelligent Systems, Smart Technologies, and User-Centric Evolution 2

Navigating the Landscape of Intelligent Systems, Smart Techn...

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2nd International Conference on Intelligent data Communication Technologies and Internet of Things, IDCIoT 2024

作者： Komatireddy, Sanjay Reddy Krishna Bhargavi, Y. Gokaraju Rangaraju Institute of Engineering and Technology Dept. of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350327533

Human-computer Interaction (HCI) is a dynamic field pi votal in shaping human-Technology relationships. HCI is a multidisciplinary field, essential in understanding and enhancing the interaction between humans and technology. Challenges within HCI encompass design, usability, accessibility, and emotional resonance. The aim of this research study is to highlight the multifaceted nature of HCI, offering insights into its transformative and complementing potential and its continuous influence on the digital landscape. By delving into the challenges faced and the current technologies (Multimodal Affect Recognition, Artificial Intelligence, etc.), this review serves as a foundation for further research and development in this vital domain, offering valuable insights into the dynamic HCI landscape. © 2024 IEEE.

关键词： Affect Recognition Human-computer Interaction (HCI) Multimodal Interaction Personalization Psychology Usability Challenges

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Neural Harvest : Advancements in Crop Yield Forecasting 7

Neural Harvest : Advancements in Crop Yield Forecasting

引用

7th International Conference on Inventive Computation Technologies, ICICT 2024

作者： Seelam, Srinivasa Reddy Thivari, Charitha Sai Parabattina, Bhagath Narendra Kumar, G. Sumanth, K. Lakireddy Bali Reddy College of Engineering Dept. of Computer Science And Engineering Mylavaram India

ISBN: (纸本)9798350359299

Crop yield forecasting involves predicting the amount of crops that a farmer can expect from their field. This prediction is based on several factors, including soil type and environmental conditions. It is a crucial issue for the farming industry, which is the backbone of any nation's economy. Thanks to advancements in Artificial Intelligence, farmers can benefit from accurate crop yield estimations. This research study presents a Feed Forward Neural Network architecture that enables farmers to get accurate crop yield estimates and finally discusses about the implementation of the procedure and its outcome. © 2024 IEEE.

关键词： Feedforward neural networks

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Respiratory Estimation During Sleep Using dept. Camera in Real Environment 13

Respiratory Estimation During Sleep Using Depth Camera in Re...

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13th IEEE Global Conference on Consumer Electronic, GCCE 2024

作者： Kushida, Daisuke Kodani, Ryuga Tottori University Faculty of Engineering Dept. Electorical Engineering and Computer Science Tottori Japan Tottori University Graduate School of Sustainability Science Dept. Engineering Tottori Japan

ISBN: (纸本)9798350355079

Sleep apnea syndrome (SAS) is common but people are generally unaware of this condition, as it occurs during sleep. A method was previously proposed to estimate respiration during sleep in a non-contact and non-constraint manner using a dept. camera that is suitable for everyday use. The method was validated on subjects who were awake but remains untested under sleeping conditions. In this study, 12 men aged 65 years or older were tested under actual sleeping conditions for eight days. The effectiveness and accuracy of the proposed method were confirmed through a comparison with commercially available products. © 2024 IEEE.

关键词： Sleep research

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A Review on Phishing Threats and data Securityin Online Trading Systems using Artificial Intelligence Techniques 2

A Review on Phishing Threats and Data Securityin Online Trad...

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2nd IEEE International Conference on Advances in Information Technology, ICAIT 2024

作者： Murugun, S. Haniah, Sheikh Koti, Shambhavi M. Sahani, Saurav Shekhar, S.N. Dept. of Computer Science and Engineering Sri Venkateshwara College of Engineering Bengaluru562157 India

ISBN: (纸本)9798350383867

Phishing threats pose significant risks to online trading systems, threatening the security and integrity of financial transactions. In this paper, we present a comprehensive review of phishing threats and data securityin online trading systems, focusing on the application of artificial intelligence (AI) techniques for detection andprevention. We discuss the evolving landscape of online trading, highlighting the risks associated with technological disruptions, malware, and phishing attacks. The paper explores various AI-based approaches, including machine learning and natural language processing, for detecting and mitigating phishing threats in real time. Additionally, we review recent studies on phishing classification techniques, AI-enabled detection mechanisms, cyber security awareness training, and deep learning-based approaches for phishing detection. Through a systematic review of existing literature, we identify challenges such as data availability, model interpretability, and scalability, and propose future research directions to enhance cyber security defenses against evolving phishing threats in online trading systems. Furthermore, we are Enhancing user education and awareness which plays a crucial role in effectively combating phishing attacks. Also, highlighting the need for collaboration between industry stakeholders, policymakers, and researchers to develop effective strategies for protecting online traders and investorsfrom financial fraud and identity theft. © 2024 IEEE.

关键词： Phishing

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FOOTBALL data ANALYSIS: THE PREDICTIVE POWER OF EXPECTED GOALS 25

FOOTBALL DATA ANALYSIS: THE PREDICTIVE POWER OF EXPECTED GOA...

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25th International Conference on Intelligent Games and Simulation, GAME-ON 2024

作者： Roccetti, Marco Berveglieri, Filippo Cappiello, Giuseppe Dept. of Computer Science and Engineering University of Bologna Italy Dept. of Management University of Bologna Italy

ISBN: (纸本)9789492859327

Major football events, such as the World Cup, have popularized the European football (i.e., soccer) beyond its traditional geographical borders, for example with a growing number of Americans who have begun to incorporate European football into their daily sport consumption. Many video game series based on this sport have further contributed to this increasing development. Not only that, but many performance indicators inspired by football computer games have become metrics that are now part of the normal conversation about real football, being used to analyse tactics, teams and players. Among these indicators, of prominent importance is the role of expected goals (xG) that measure the quality of a shot by calculating the likelihood that it will be scored from a particular position during a particular phase of play. Often, someone talks about xG leading to imprecise conclusions and to a distorded point of view on this performance indicator. In this paper, using a non-parametrical Kolmogorov Smirnov hypothesis testing method, we show that there is no statistically significant difference if, in a given football tournament, the final scores are awarded to the participating teams either with real goals or based on xGs, thus demystifying some wrong assumptions about this indicator. data for this study come from all the matches played during the 2020 UEFA European Football Championship. © 2024 25th International Conference on Intelligent Games and Simulation, GAME-ON 2024. All rights reserved.

关键词： Predictive analytics

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