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检索条件"丛书名=Communications in Computer and Information Science"

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Online Bottleneck Matching on a Ring 42nd

Online Bottleneck Matching on a Ring

引用

42nd National Conference on Theoretical computer science

作者： Xiao, Man Li, Weidong Yunnan Univ Sch Math & Stat Kunming 650504 Yunnan Peoples R China

ISBN: (纸本)9789819614899;9789819614905

On a ring, given m servers and m requests arriving one by one in an online fashion. Upon each request arrival, it needs to be immediately matched to a server, generating a matching distance on the ring. The objective is to find a matching where each server and each request are strictly matched once, minimizing the maximum matching distance. When the m servers are evenly distributed on the ring, we prove that the classical greedy algorithm achieves an optimal competitive ratio of m. When m = 3, using polar coordinates to partition the ring into three intervals, we provide optimal online algorithms for four parameter scenarios where the competitive ratio depends on the server spacing ratio.

关键词： Online bottleneck matching Ring Partition Online algorithm

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Orthogonal Activation Functions in Neural Networks: Utilizing Chebyshev, Legendre, and Hermite Polynomials 8th

Orthogonal Activation Functions in Neural Networks: Utilizin...

引用

2024 World Congress in computer science, computer Engineering and Applied Computing-CSCE

作者： Safaei, Saeid Rasheed, Khaled Taha, Thiab Safaei, Vahid Arpinar, Budak Gutierrez, Juan B. Arabnia, Hamid R. Univ Georgia Sch Comp Athens GA USA Univ Isfahan Dept Mech Engn Esfahan Iran Univ Texas San Antonio Dept Math San Antonio TX 78249 USA

ISBN: (纸本)9783031856273;9783031856280

In this study, we explore the potential of orthogonal polynomial functions as activation functions within the SWAG neural network architecture. By employing Chebyshev, Legendre, Hermite polynomials and and sinusoidal functions, we conduct a rigorous comparative analysis to evaluate the performance enhancements across a range of benchmark datasets. Furthermore, this paper investigates the influence of factorial coefficients on the performance of these models, providing a nuanced understanding of how these mathematical modifications affect learning dynamics and model efficacy. Our results offer insights into optimizing neural network architectures through advanced mathematical functions.

关键词： neural networks orthogonal polynomials activation functions Chebyshev polynomials Legendre polynomials Hermite polynomials

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Smart Chatbot for the Optimization of the Use of Natural Resources in Agricultural Production

Smart Chatbot for the Optimization of the Use of Natural Res...

引用

4th International Conference on Advanced Research in Technologies information Innovation and Sustainability-ARTIIS-Annual

作者： Silva, Jefferson Ronceros, Carlos Mansilla-Lopez, Juan Univ Peruana Ciencias Aplicadas Lima Peru

ISBN: (纸本)9783031834349;9783031834356

Agriculture is the main activity by which most Peruvians in rural areas manage to subsist. Making the proper use of natural resources such as water, land or climate in agricultural production can generate greater profitability by reducing costs and increasing units of agricultural products, but currently farmers get this information through family, friends, or through platforms such as Google or Youtube. The present study was developed with the objective of providing assistance focused on the optimization of natural resources through a conversational flow provided by the chatbot mobile application "AIgrary", which can be used in rural coastal areas of Lima. It is designed for Android devices and uses Dialogflow platforms for conversational flow interaction with the user through Nat- ural Language Processing, and uses Firebase for hosting user accounts. For the validation of this Chatbot, a presentation of the mobile application was made to 10 participating farmers from the province of Huaral in Lima, to then request the completion of surveys to measure User Satisfaction and Usability of the System. In addition, search times of "AIgrary" were compared with platforms such as Google and Youtube. The results within the surveys show a 94.6% of User Satisfaction and 96.0% of System Usability, and the response search time in "AIgrary" was only 1 s.

关键词： Chatbot agriculture natural resources natural language processing

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In-Vehicle Sensing Platform for the Inference of Older Drivers' Mild Cognitive Condition 8th

In-Vehicle Sensing Platform for the Inference of Older Drive...

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2024 World Congress in computer science, computer Engineering and Applied Computing-CSCE

作者： Moshfeghi, Sonia Jang, Jinwoo Jan, Muhammad Tanveer Ghoreishi, Seyedeh Gol Ara Furht, Borko Yang, Kwangsoo Tappen, Ruth Newman, David Conniff, Joshua Rosselli, Monica Florida Atlantic Univ Coll Engn & Comp Sci Boca Raton FL 33431 USA Florida Atlantic Univ Christine E Lynn Coll Nursing Boca Raton FL 33431 USA Florida Atlantic Univ Charles E Schmidt Coll Sci Boca Raton FL 33431 USA

ISBN: (纸本)9783031856273;9783031856280

Changes in the driving behavior of older drivers can be indicative of conditions of mild cognitive impairment (MCI), which affect their memory and recognition skills on the road. Traditional clinical evaluations cover only a limited subset of cognitively impaired drivers, prompting the need for innovative technologies to monitor the cognitive status of older drivers routinely. In this study, we developed in-vehicle sensing devices capable of capturing vehicular data streams that reveal older drivers' driving patterns. Using K-means clustering on preprocessed and scaled data, we identified four distinct driver profiles characterized by trip frequency, driving style, and demographic factors. These profiles ranged from active, frequent travelers to sedentary, cautious drivers, with significant differences in trip duration, distance, and vehicle operation metrics such as speed and engine load. A developed random forest model further identified peak hour trips, age, gender, and ambient temperature as significant predictors of MCI, highlighting the complex interplay between lifestyle, driving behaviors, and demographics.

关键词： Mild cognitive impairement Older drivers Driving behavior

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Proposal of a Double Feedback Digital Product Ranking System 1st

Proposal of a Double Feedback Digital Product Ranking System

引用

1st International Workshop on Mechanism Design in Social Networks

作者： Liu, Yuchen Hadfi, Rafik Ito, Takayuki Kyoto Univ Dept Social Informat Kyoto Japan

ISBN: (纸本)9789819602131;9789819602148

This research proposal outlines a novel mechanisms designed to optimize the ranking order of digital products, primarily focusing on movies, TV series, and video games. The aim here is to develop a more objective quality measurement for digital products, which are typically more challenging to assess compared to physical products. The proposed mechanism, named the "Double Feedback Digital Product Ranking System", uses product's quality and customer's preferences to optimize products' listed ranking. This research relies on semantic analysis and label classification to process text reviews, and on Large Language Models (LLMs) to represent customer preferences. By refining the estimation of user preferences and product quality, online marketplaces can rank products in a more justified order for each customer, and customers will have more chances to purchase suitable products, potentially enhancing collective customer satisfaction. The main hypothesis will be tested through a multiagent system simulation that models the dynamics of the marketplace, sellers, and customers, providing a comprehensive evaluation of the system's impact on online digital product platforms.

关键词： Digital elevation model

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Bid Intercession to Unlock Human Control in Decentralized Consensus-Based Multi-robot Task Allocation Algorithms 4th

Bid Intercession to Unlock Human Control in Decentralized Co...

引用

4th Workshops on Agents and Robots for Reliable Engineered Autonomy

作者： Guillet, Victor Grand, Christophe Lesire, Charles Picard, Gauthier Univ Toulouse DTIS ONERA Toulouse France

ISBN: (纸本)9783031731792;9783031731808

We investigate the introduction of novel intercession mechanisms in consensus-based decentralized task allocation within a heterogeneous multi-agent fleet. Intercession refers to the principle of agents biding on behalf of other agents or imposing certain allocations in decision-making architectures leveraging auction-based decision strategies. This is particularly relevant in settings where human operators, having more precise knowledge of the system situation, want to steer or force the multi-robot task allocation (MRTA). We thus extend an existing consensus framework, consensus-based auction algorithm (CBAA), while offering a simple generic method that operates independently of the underlying reasons, enabling interventions in a decentralized coordination process by humans at the agent and task levels. These interventions, whether systematic or occasional, have the added benefit of incurring minimal computational costs for field agents while maintaining the underlying algorithm's convergence and performance properties. We experimentally evaluate the proposed algorithm, I-CBAA, on synthetic MRTA scenarios implemented using the ROS framework.

关键词： Consensus-Based Auctions Mixed Initiative Multi-Robot Task Allocation

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Obstacles that Limit Innovation in Activities Related to Ecuador's Productive Sectors MSMEs 4th

Obstacles that Limit Innovation in Activities Related to Ecu...

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4th International Conference on Advanced Research in Technologies information Innovation and Sustainability-ARTIIS-Annual

作者： Morales-Molina, Tania Silva-Ordonez, Catalina Salazar-Mera, Juan Mora-Rosales, Jose Univ Indoamer Ambato Ecuador

ISBN: (纸本)9783031840777;9783031840784

This paper studies the main obstacles that limit innovation in activities related to productive sectors in Ecuadorian companies with less than 200 workers (micro, small and medium-sized enterprises, MSMEs). The aim is to identify those obstacles that directly keep the sectorial innovation from growing. The study used a quantitative and explanatory analysis using the results presented by the Superintendency of Companies of Ecuador at the end of 2023. At the national level, there were the following numbers of companies: Micro (62,724), Small (21,305) and Medium (6,135). The results show that companies are working inefficiently in relation to growth in innovation, representing current technological challenges. The conclusions present proposals and recommendations for micro-entities to survive and compete better in the current environment, through a guide of good practices that will positively influence the innovation and modernization of their companies.

关键词： Growth Innovation Productive Sectors

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Design of IoT Enabled Smart Sensor System for In-situ Black Pepper Plant Health Monitoring Using Deep Learning Model 2nd

Design of IoT Enabled Smart Sensor System for In-situ Black ...

引用

2nd International Conference on Agriculture-Centric Computation

作者： Ranjan, Saurabh Kumar Sathiya, S. Natl Inst Technol Dept Elect Engn Calicut Kozhikode India

ISBN: (纸本)9783031744396;9783031744402

This paper presents the health monitoring system and early detection of disease in black pepper plants by integrating an IoT-enabled smart sensor system with a transfer learning based Convolutional Neural Network (CNN) model. The system is designed to continuously monitor essential parameters influencing plant growth, such as temperature, humidity, soil nutrients, and moisture levels, while simultaneously detecting infectious diseases. Utilizing the pre-trained VGG16 architecture, the CNN model is fine-tuned to classify diseases based on leaf images. Experimental findings demonstrate that the transfer learning model surpasses conventional CNNs, exhibiting superior accuracy across training, testing, and validation datasets. The proposed system serves as a valuable tool for farmers, empowering them to make informed decisions and implement timely interventions, thereby enhancing crop health and yields in black pepper cultivation.

关键词： Black pepper IoT Sensors CNN transfer learning VGG16

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Evaluating the Impact of Combinatorial Interaction Testing on Test Automation: A Case Study from Industry 33rd

Evaluating the Impact of Combinatorial Interaction Testing o...

引用

33rd International Conference on Software and Data Engineering

作者： Daoud, Feras Bures, Miroslav David, Zdenek Syrovatka, Petr Czech Tech Univ Prague Czech Republic

ISBN: (纸本)9783031752001;9783031752018

Software testing regularly involves numerous setups and user inputs, leading to a combinatorial explosion of test cases. While Combinatorial Interaction Testing (CIT) has been theoretically investigated, its effectiveness in real-world scenarios remains unclear [1]. This research fills that gap by utilizing CIT in some live software projects. We led two studies: the first focuses on optimizing user input testing in jTrac, and the second focused on managing system configurations in Redmine, a comparative web application. We looked at CIT to customary testing strategies, breaking down components like test design time, test automation, test execution, suite size, and defect detection. The investigation gave valuable insights into enhancing CIT execution and reception. The results are promising. With CIT, the number of required test cases is significantly reduced, but at the same time, defect detection is improved. In the first study, the average time to detect a defect was 1.40 h (design, automation, execution, and evaluation) compared to 0.35 hwith CIT. Similar patterns emerged in the second study. These findings have important implications for both researchers and organizations. They highlight CIT's promise for software testing, including decreasing test case burden and perhaps improving defect detection rates. This study provides practical evidence for organizations and testers looking to improve their testing procedures.

关键词： Combinatorial Testing Model-Based Testing Empirical Efficiency Automated Testing Unified Combinatorial Interaction Testing

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Cross-Organ Investigation of Tumor Histological Features Similarities Using Transfer Learning: A Case Study on Breast and Colorectal Tumors 4th

Cross-Organ Investigation of Tumor Histological Features Sim...

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4th International Conference on Intelligent Systems and Pattern Recognition-ISPR

作者： Helmy, Menna Al-Saady, Rafif Qatar Univ Doha Qatar

ISBN: (纸本)9783031821554;9783031821561

Breast and colorectal cancers are two of the most commonly occurring cancers in the world. Transfer Learning with models pre-trained on ImageNet has been extensively used in the literature in the detection of these two deadly diseases from histopathology images. A limited number of works have investigated cross organ histological similarities using deep learning, which showed the correlation between some breast and colorectal cancer subtypes. In this paper, we focus on a further investigation of the similarities and correlation between breast and colorectal cancers by focusing on the binary benign/malignant classification problem. We conduct a number of experiments with different training and fine-tuning strategies, leveraging transfer learning from pre-trained models. Using the different strategies, a model is trained on a breast cancer histopathology dataset, and tested on two colorectal cancer histopathology datasets. Accordingly, the results demonstrate similarities in benign and malignant tumors across the two organs, with an accuracy reaching as high as 97.33% and 98.80% on the benign and malignant colorectal samples respectively.

关键词： Breast tumor Colorectal tumor Transfer learning Histopathology Cross-organ inference

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