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25th International Arab Conference on Information Technology, ACIT 2024

作者： Momani, Mutaz Yousef, Nidal Aljawazneh, Qotadeh Issa, A.T. Abuowaida, Suhaila Alazaidah, Raed Khouj, Mohammed Talat Batyha, Radwan Elsoud, Esraa Abu Zarqa University Faculty of Information Technology Department of Computer Science Zarqa Jordan Al-Albayt University Faculty of Information Technology Department of Computer Science Mafraq Jordan Zarqa University Department of Data Science and Ai Faculty of Information Technology Zarqa Jordan University of Business and Technology Department of Electrical Engineering Jeddah21432 Saudi Arabia Private University Faculty of It Applied Science Department of Computer Science Amman Jordan

ISBN: (纸本)9798331540012

Breast cancer is the most prevalent cancer among women and can be deadly, necessitating early detection to enhance patient outcomes and treatment effectiveness. Recently, Machine Learning (ML) techniques have shown potential in medical diagnostics, especially in breast cancer screening. ML algorithms examine extensive medical databases, including patient records, to identify subtle patterns and anomalies indicative of cancer. These algorithms excel at recognizing intricate patterns that may be missed by human analysis. Thereby, increasing the precision of breast cancer diagnoses. By evaluating and analyzing medical data, ML algorithms can detect minute anomalies, facilitating early identification of potential cancer cases. A significant advantage of ML-based breast cancer detection is its capacity for continuous learning and adaptation. In this study, we utilized 34 classifiers and five feature selection methods on three datasets. The first dataset comprises 286 instances with 10 integer-type features. The second dataset includes 699 instances with 10 integer-type features, and the third dataset consists of 286 instances with 13 integer-type features. For Dataset 1, Filtered Classifier and J-48 yielded the best results, while the Bayesnet classifier performed best on Dataset 2. In Dataset 3, SimpleLogistic and LMT achieved the best outcomes. Regarding feature selection, the study showed that the GainRatioAttributeEval, InfoGainAttributeEval, and CorrelationAttributeEval techniques are the best among the feature selection methods tested in the study. © 2024 IEEE.

关键词： Lung cancer

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Protothread and Cooperative Multitasking Scheduler on the Arduino Framework 16

Protothread and Cooperative Multitasking Scheduler on the Ar...

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16th International Conference on Applied and Theoretical Electricity, ICATE 2024

作者： Avila, Bernardo Yaser Leon Vazquez, Carlos Alberto Garcia Baluja, Osmel Perez Alexandru, Marian Cotfas, Daniel Tudor Cotfas, Petru Adrian Dominguez, Luis Alberto Quintero Transilvania University of Braşov Faculty of Electrical Engineering and Computer Science Department of Electronics and Computers Braşov Romania University of Sancti Spiritus 'José Martí Pérez' Faculty of Business and Technical Sciences Department of Computer Engineering Sancti Spiritus Cuba

ISBN: (纸本)9798350388107

In the search for a simple and scalable firmware solution for Internet of Things (IoT) applications on devices with significant constraints, such as limited energy, hardware resources, and cost, numerous well-recommended and widely used solutions, including Contiki and RIOT, can be identified. Despite their merits, these solutions often present challenges when deployed on popular boards, such as the Arduino or ESP32/8266. This paper synthesizes diverse experiences and introduces idOS, a cooperative task scheduler featuring protothreads, timers, power management, and a TCP/IP network stack atop the Arduino framework, with a particular focus on users interested in IoT applications. This work examines the motivations, philosophy, structure, and limitations of idOS, offering insights into its development and potential applications. © 2024 IEEE.

关键词： Firmware

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Evaluating collaborative rationality-based decisions: A literature review

Evaluating collaborative rationality-based decisions: A lite...

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2022 International Conference on ENTERprise Information Systems, CENTERIS 2022 - International Conference on Project MANagement, ProjMAN 2022 and International Conference on Health and Social Care Information Systems and Technologies, HCist 2022

作者： Elgendy, Nada Elragal, Ahmed Päivärinta, Tero M3S Faculty of Information Technology and Electrical Engineering University of Oulu Finland Department of Computer Science Electrical and Space Engineering Lulea University of Technology Sweden

Decision making has evolved throughout the years, nowadays harnessing massive amounts and types of data through the unprecedented capabilities of data science, analytics, machine learning, and artificial intelligence. This has potentially led to higher quality and more informed decisions based on the collaborative rationality between humans and machines, no longer bounded by the cognitive capacity and limited rationality of each on their own. However, the multiplicity of modes of collaboration and interaction between humans and machines has also increased the complexity of decision making, consequentially complicating ex-Ante and ex-post decision evaluation. Nevertheless, evaluation remains crucial to enable human and machine learning, rationalization, and sensemaking. This paper addresses the need for more research on why and how to evaluate collaborative rationality-based decisions, setting the stage for future studies in developing holistic evaluation solutions. By analyzing four relevant streams of literature: 1) classical decision theory and organizational management, 2) cognitive and neuroscience, 3) AI and ML, and 4) data-driven decision making, we highlight the limitations of current literature in considering a holistic evaluation perspective. Finally, we elaborate the theoretical underpinnings from the knowledge base on how humans and machines evaluate decisions, and the considerations for evaluating collaborative rationality-based decisions. © 2023 Elsevier B.V.. All rights reserved.

关键词： Decision making

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Experiences in PCB manufacturing with ultra-lowcost and home-made CNC machine 16

Experiences in PCB manufacturing with ultra-lowcost and home...

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16th International Conference on Electronics, computers and Artificial Intelligence, ECAI 2024

作者： Avila, Bernardo Yaser LeON Vazquez, Carlos Alberto GarcIA Baluja, Osmel PERez Dominguez, Luis Alberto Quintero Cotfas, Daniel Tudor Cotfas, Petru Adrian Transilvania University of Braşov Faculty of Electrical Engineering and Computer Science Department of Electronics and Computers Braşov Romania University of Sancti Spiritus 'José Martí Pérez' Faculty of Business and Technical Sciences Department of Computer Engineering Sancti Spiritus Cuba

ISBN: (纸本)9798350371154

In the context of printed circuit board (PCB) manufacturing, accessibility and affordability are pivotal, especially for individuals and institutions with limited financial resources. The advent of ultra-low-cost and homemade computer numerical control (CNC) machines offers a promising solution to address these concerns. However, the plethora of online resources often presents solutions fraught with practical challenges. This paper delves into firsthand experiences in utilizing such technologies, navigating the delicate balance between cost-effectiveness and functionality in prototyping. By examining the inherent obstacles, it aims to offer valuable insights for those seeking to achieve PCB manufacturing goals with minimal resources. © 2024 IEEE.

关键词： Cost effectiveness

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Enhancing Physical-Layer Security in Full-Duplex Cooperative Wireless Networks over α-μ Fading Channels 7

Enhancing Physical-Layer Security in Full-Duplex Cooperative...

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7th International Conference on Advanced Communication Technologies and Networking, CommNet 2024

作者： Saddouq, Ayam Al-Mistarihi, Mamoun F. Khoderi, Mahmoud A. Darabkh, Khalid A. Jordan University of Science and Technology Faculty of Engineering Electrical Engineering Department P.O. Box 3030 Irbid Jordan The University of Jordan School of Engineering Computer Engineering Department Amman11942 Jordan

ISBN: (纸本)9798350367027

Cooperative communication is an emerging method that allows devices with a single antenna to share their antennas and assist other nodes in transmitting signals. This leads to enhanced spatial diversity, lower power consumption, and increased reliability of signal reception. This study uses full-duplex mode and α-μ fading channels and derives the secrecy outage probability for a single relay to assess the system's secrecy performance and examine how utilizing jamming signals affects system security. Theoretical results for the derived expression are given. © 2024 IEEE.

关键词： Cooperative communication

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Optimizing Web Server Performance: A Comparative Analysis of Central Manager and Round Robin Load Balancing Algorithms 4

Optimizing Web Server Performance: A Comparative Analysis of...

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4th International Conference on electrical engineering and computer science, ICECOS 2024

作者： Permana Arrasyid, Fahmi Stiawan, Deris Afifah, Nurul Heryanto, Ahmad Azhar, Iman Saladin B. Bardadi, Ali Yudho Suprapto, Bhakti Pahendra Anto Saputra, Iwan Sriwijaya University COMNETS Rerearch Group Faculty of Camp. Science Palembang Indonesia Sriwijaya University Faculty of Comp. Science Computer Engineering Dept. Palembang Indonesia Sriwijaya University Faculty of Comp. Science Information System Dept. Palembang Indonesia Sriwijaya University Faculty of Engineering Electrical Engineering Dept. Palembang Indonesia

ISBN: (纸本)9798350368253

Central manager algorithm has a lower average throughput compared to the round robin algorithm. This is evidenced by a significant decrease in throughput values during measurements. Central manager algorithm provides a faster average response time than round robin algorithm, despite experiencing an increase in response time values over time. Central manager algorithm shows a higher request loss rate and many requests are not served. Under normal performance conditions, both algorithms yield the same average request loss rate, achieving stable values without failed requests. The central manager algorithm ensures relatively balanced resource availability, including CPU and memory usage, across each slave web server compared to the round robin algorithm. The results show that increasing the number of clients and client requests during system testing to better observe server resource availability and load distribution performance. For future research, it is recommended to increase the number of clients in the system testing to enhance server load and to introduce client request actions on the web server to further highlight resource availability on each web server. © 2024 IEEE.

关键词： Response time (computer systems)

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Using Stable Diffusion Model for Text-Driven Generation in Augmented Reality Applications 33rd

Using Stable Diffusion Model for Text-Driven Generation in A...

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33rd International Conference on Organization and Technology of Maintenance, OTO 2024

作者： Rücker, Kristian Livada, Časlav Galba, Tomislav Baumgartner, Alfonzo Faculty of Electrical Engineering Josip Juraj Strossmayer University in Osijek Computer Science and Information Technology Osijek Kneza Trpimira 2B Osijek31000 Croatia

ISBN: (纸本)9783031805967

Rapid advances in science and technology have led to the integration of artificial intelligence (AI) in many areas, including augmented reality (AR). This study explores the application of the Stable Diffusion (SD) model to develop an AR application that generates images based on text descriptions. Using Unity, a versatile game development platform, we implemented this AR application, scripting in C# with Visual Studio 2022. The user interface and functionality of the SD model were managed via the UI Stable Diffusion Automatic 1111 tool, allowing seamless integration and execution of SD functions. This work demonstrates the potential of AI-driven models in enhancing AR experiences and introduces a novel approach to dynamic visual content creation and editing. Furthermore, this technology has significant implications for the maintenance of municipal infrastructure and maintenance organizations. By converting text instructions into visual AR overlays, maintenance teams can improve the accuracy and efficiency of tasks such as inspections, repairs, and infrastructure management, streamlining operations and reducing errors. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Augmented reality

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Leveraging ChatGPT for enhanced stock selection and portfolio optimization

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Neural Computing and Applications 2025年第8期37卷 6163-6179页

作者： Huang, Zhendai Liao, Bolin Hua, Cheng Cao, Xinwei Li, Shuai College of Computer Science and Engineering Jishou University Jishou416000 China School of Business Jiangnan University Wuxi214122 China Faculty of Information Technology and Electrical Engineering University of Oulu Oulu90570 Finland VTT-Technology Research Center of Finland Kaitovayla 1 Oulu90570 Finland

The public release of ChatGPT represents a significant milestone in generative AI technology, enabling the autonomous generation of content based on pre-training. This breakthrough presents new opportunities for advancements in the field of portfolio selection. This paper aims to introduce a comprehensive portfolio selection method by applying ChatGPT for stock selection and combining it with optimization algorithms to jointly optimize portfolio selection. Compared to randomly selected stocks, the portfolios optimized using ChatGPT-selected stocks and solved with the egret swarm optimization algorithm (ESOA) demonstrate higher diversification and lower volatility, leading to superior portfolio optimization results. Additionally, to validate ESOA’s superiority, its performance is compared against genetic algorithm (GA) and particle swarm optimization (PSO) on five metrics: risk, expected return, Sharpe ratio, objective value, and penalty term. Under equivalent experimental setting, ESOA exhibits a better ability to balance the relationship between risk and return. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Optimization algorithms

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Elite-guided equilibrium optimiser based on information enhancement:Algorithm and mobile edge computing applications

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CAAI Transactions on Intelligence Technology 2024年第5期9卷 1126-1171页

作者： Zong-Shan Wang Shi-Jin Li Hong-Wei Ding Gaurav Dhiman Peng Hou Ai-Shan Li Peng Hu Zhi-Jun Yang Jie Wang School of Information Science and Engineering Yunnan UniversityKunmingChina Shenzhen Institute for Advanced Study University of Electronic Science and Technology of ChinaShenzhenChina Academic Affairs Office Yunnan University of Finance and EconomicsKunmingChina Faculty of Management and Economics Kunming University of TechnologyKunmingChina Department of Electrical and Computer Engineering Lebanese American UniversityBeirutLebanon Department of Computer Science and Engineering University Centre for Research and DevelopmentChandigarh UniversityChennaiIndia Department of Computer Science and Engineering Graphic Era Deemed to Be UniversityDehradunIndia School of Computer Science Fudan UniversityShanghaiChina Rackham Graduate School University of MichiganAnn ArborMIUSA Research and Development Department Youbei Technology Co.LTDKunmingChina School of Mechanical and Power Engineering Zhengzhou UniversityZhengzhouChina

The Equilibrium Optimiser(EO)has been demonstrated to be one of the metaheuristic algorithms that can effectively solve global optimisation *** the paradox between exploration and exploitation operations while enhancing the ability to jump out of the local optimum are two key points to be addressed in EO *** alleviate these limitations,an EO variant named adaptive elite-guided Equilibrium Optimiser(AEEO)is ***,the adaptive elite-guided search mechanism enhances the balance between exploration and *** modified mutualism phase reinforces the information interaction among particles and local optima *** cooperation of these two mechanisms boosts the overall performance of the basic *** AEEO is subjected to competitive experiments with state-of-the-art algorithms and modified algorithms on 23 classical benchmark functions and IEE CEC 2017 function test *** results demonstrate that AEEO outperforms several well-performing EO variants,DE variants,PSO variants,SSA variants,and GWO variants in terms of convergence speed and *** addition,the AEEO algorithm is used for the edge server(ES)placement problem in mobile edge computing(MEC)*** experimental results show that the author’s approach outperforms the representative approaches compared in terms of access latency and deployment cost.

关键词： ANT COLONY optimization CLOUD COMPUTING GENETIC ALGORITHMS SWARM intelligence

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Robust Multiresolution and Multistain Background Segmentation in Whole Slide Images 23rd

Robust Multiresolution and Multistain Background Segmentatio...

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Proceedings of the 23rd Polish Conference on Biocybernetics and Biomedical engineering, PCBEE 2023

作者： Jurgas, Artur Wodzinski, Marek Atzori, Manfredo Müller, Henning Information Systems Institute Sierre Switzerland Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering AGH University of Science and Technology Krakow Poland Department of Neuroscience University of Padova Padova Italy Medical Faculty University of Geneva Geneva Switzerland

ISBN: (纸本)9783031384295

Background segmentation is an important step in analysis of histopathological images. It allows one to remove irrelevant regions and focus on the tissue of interest. However, background segmentation is challenging due to the variability of stain colors and intensity levels across different images, modalities, and magnification levels. In this paper, we present a learning-based model for histopathology background segmentation based on convolutional neural networks. We compare two multiresolution approaches to deal with the variability of magnification in histopathology images: (i) model that uses upscaling of smaller patches of the image, and (ii) model simultaneously trained on multiple resolution levels. Our model is characterized by solid performance both in multiresolution and multistain dyes (H &E and IHC), achieving good performance on publicly available dataset. The quantitative scores are, in terms of the Dice score, close to 94.71. The qualitative analysis presents strong performance on previously unseen cases from different distributions and various dyes. We freely release the model, weights, and ground-truth annotations to promote the open science and reproducible research. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Pathology

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