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共 15923 条记录，以下是281-290 订阅

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Automated Biofloc Technology for Fish Farming with GSM based Monitoring System 3

Automated Biofloc Technology for Fish Farming with GSM based...

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3rd IEEE international conference on robotics, Automation, Artificial-intelligence and Internet-of-Things, RAAICON 2024

作者： Hassain, Md Mehedi Gani, Muhammad Osman Rahman, Abdur Hasnat, S.M. Rahbar Abdullah International Islamic University Chittagong Dept. of Electrical & Electronics Engineering Chittagong Bangladesh East Delta University Dept. of Electrical & Electronics Engineering Chittagong Bangladesh

ISBN: (纸本)9798331534400

Biofloc technology mitigates aquaculture's environmental impact by using microbial flocs to convert organic waste into nutrient rich feed. To enhance water quality management, our research focuses on a GSM based monitoring system for real time data collection and analysis. The system integrates pH, temperature, and ultrasonic sensors with an Arduino Uno microcontroller, GSM module, servo, and pump motors to monitor and regulate water quality. The system measures timely and crucial data on water quality, including parameters such as temperature, pH levels, and the state of the feeding box. The pH and temperature sensors provide analog readings, while the ultrasonic sensor monitors feeding box levels. Food management is controlled by a servo motor that operates the feeding box, and a pump motor maintains water quality. The system uses temperature and pH sensors for rapid hazard detection, minimizing ammonia and nitrite buildup risks. The GSM module enables real time data connectivity, allowing users to track and control system operations remotely. This study empowers fish farmers and hobbyists with real-time water quality data, promoting informed decision-making to enhance aquatic health and productivity. It offers valuable insights to the broader aquaculture community. © 2024 IEEE.

关键词： Decision making

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Customer Churn Prediction: Leveraging Data analysis and Machine Learning Approaches 10

Customer Churn Prediction: Leveraging Data Analysis and Mach...

引用

10th international conference on Artificial intelligence and robotics, QICAR 2024

作者： Mardi, Arsalan Ghorbani, Hananeh Faculty of Electricity Computer Information Technology and Biomedical Engineering Qazvin Branch Islamic Azad University Qazvin Iran Faculty of Science and Engineering Bandar-e Anzali Branch Islamic Azad University Gilan Iran

ISBN: (纸本)9798350348873

The prediction of customer attrition in the banking industry has gained significant attention due to the proliferation of services and the need to retain customers in today's competitive market, particularly when customers abandon banking products and services. Customer churn, defined as the termination of a customer's relationship with a bank, has become a critical concern. Changing the banks' approach is crucial, emphasizing the importance of retaining and ensuring customer loyalty, especially when customers discontinue their usage of banking services and products. Banks must actively determine customer attrition by analyzing customer behavior and making efforts and investments to retain customers. This study uses different machine learning algorithms and leverages data from the banking sector to achieve precision in predicting customer loss. This endeavor leads to the empowerment of financial institutions, enabling the implementation of precision-targeted measures aimed at cultivating the preservation of customer loyalty. Before applying machine learning algorithms, data is processed for data cleansing and transformation to ensure data quality. The results indicate that LightGBM and RandomForest algorithms exhibit the best performance in detecting customer attrition. ©2024 IEEE.

关键词： Forecasting

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Towards Symbiotic Creativity: A Methodological Approach to Compare Human and AI Robotic Dance Creations 32

Towards Symbiotic Creativity: A Methodological Approach to C...

引用

32nd international Joint conference on Artificial intelligence (IJCAI)

作者： De Filippo, Allegra Giuliani, Luca Mancini, Eleonora Borghesi, Andrea Mello, Paola Milano, Michela Univ Bologna DISI Bologna Italy

ISBN: (纸本)9781956792034

Artificial intelligence (AI) has gradually attracted attention in the field of artistic creation, resulting in a debate on the evaluation of AI artistic outputs. However, there is a lack of common criteria for objective artistic evaluation both of human and AI creations. This is a frequent issue in the field of dance, where different performance metrics focus either on evaluating human or computational skills separately. This work proposes a methodological approach for the artistic evaluation of both AI and human artistic creations in the field of robotic dance. First, we define a series of common initial constraints to create robotic dance choreographies in a balanced initial setting, in collaboration with a group of human dancers and choreographer. Then, we compare both creation processes through a human audience evaluation. Finally, we investigate which choreography aspects (e.g., the music genre) have the largest impact on the evaluation, and we provide useful guidelines and future research directions for the analysis of interconnections between AI and human dance creation.

关键词： robotics

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An Overview of Optimized Inventory Management Models in Technology Companies: Historical Developments, Practical Applications, and AI-Driven Approaches 7

An Overview of Optimized Inventory Management Models in Tech...

引用

7th international conference on Algorithms, Computing and Artificial intelligence, ACAI 2024

作者： Arnawtee, Mohammed Mahde Mahmood Zaiter, Murooj Fadhil Zaiter Institute of radio electronics and information technologies Ural Federal University Dept. Big Data Analysis and Methods of Analysis Ekaterinburg Russia

ISBN: (纸本)9798331529314

This article provides a comprehensive overview of improved inventory management models in technology companies and how AI methodologies such as machine learning, predictive analytics, and optimization algorithms are revolutionizing inventory management by enabling real-time decision making, accurate demand forecasting, and automated inventory replenishment by integrating historical context with state-of-the-art AI techniques. This article provides a thorough understanding of how technology companies can leverage advanced inventory management models to maintain a competitive edge and challenges associated with implementing AI- driven inventory systems. The findings offer valuable insights for both industry practitioners and academics, contributing to the development of more resilient and adaptive inventory management strategies within the rapidly evolving technology sector. © 2024 IEEE.

关键词： Inventory control

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ICACS 2024 - Proceedings of the 2024 8th international conference on Algorithms, Computing and Systems

ICACS 2024 - Proceedings of the 2024 8th International Confe...

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8th international conference on Algorithms, Computing and Systems, ICACS 2024

ISBN: (纸本)9798400718304

The proceedings contain 24 papers. The topics discussed include: autonomous floating garbage collection device using computer vision and robotics;coordinated optimization of scheduling and path planning for delivery robots in intelligent manufacturing workshops;a preliminary study of the stressed and drowsy driving prediction models using semi-supervised learning;axial capacity prediction of concrete externally strengthened by low-cost natural fiber reinforced polymer composite utilizing machine learning intelligence;enhancing brain tumor diagnosis: a cutting-edge ensemble deep learning approach;a comparative study of sentiment analysis on twitter and reddit using deep learning techniques;generative artificial intelligence for future education: current research status, hot spots, and research trends;methodological considerations for anonymizing tabular data using generative adversarial networks;and data migration in large scale storage systems with varying file sizes.

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Design of Fertilizer analysis System for Precision Fertilizer Application 4

Design of Fertilizer Analysis System for Precision Fertilize...

引用

4th international conference on Artificial intelligence, robotics, and Communication, ICAIRC 2024

作者： Wei, Qiang Lang, Chunling Lu, Fei Chen, Yuer Huang, Yu Mo, Kaining Guangxi Science & Technology Normal University Laibin China

ISBN: (纸本)9798331531225

The traditional fertilizer application method relies on experience to apply fertilizer on a large scale, which has problems such as fertilizer waste and environmental pollution, and affects the sustainable development of agriculture. For this reason, this paper designs and realizes a set of precision fertilizer application control systems containing sensors, decision-making, and positioning systems. Among them, the sensor system senses the real-time crop and soil status through soil moisture sensors, temperature sensors, and crop growth sensors;the decision-making system uses a high-performance processor, a variety of data transmission interfaces, data processing, and storage modules, and decision-making algorithm execution units to process and analyze the sensor data and generate the decision of fertilizer application. The localization system is based on the hardware of LIDAR, development boards, etc., as well as the SLAM map building, and AMCL positioning algorithm to achieve accurate positioning;through these three systems to fully regulate the fertilization to achieve precision fertilization. © 2024 IEEE.

关键词： Fertilizers

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Fault Diagnosis of Quadruped Robot Joint Modules Based on TDIC and Random Forest 5

Fault Diagnosis of Quadruped Robot Joint Modules Based on TD...

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5th international conference on Sensing, Measurement and Data Analytics in the Era of Artificial intelligence, ICSMD 2024

作者： Chen, Yufan Fan, Beibei Xiong, Xin Shi, Mapping School of Mechatronic Engineering and Automation Shanghai University Shanghai China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai China

ISBN: (纸本)9798331529192

As robotics technology advances, quadruped robots are increasingly instrumental in diverse applications, including rescue operations and healthcare. However, the intricate operating conditions expose the components within the joint modules of these robots to alternating and impact loads. Consequently, research into signal processing and fault diagnosis techniques for planetary gearboxes in joint modules holds significant engineering importance. Given the challenges associated with fault signal extraction from planetary gearboxes, this study proposes a novel fault feature extraction method based on Time-Dependent Intrinsic Correlation (TDIC), integrated with a random forest classifier for fault classification. This approach leverages signal frequency analysis to adaptively extract segments characterized by high correlation among different physical field signals as fault features. The random forest model is utilized for fault classification and its performance is compared against CNN, KNN, and XGBoost models. Experimental results validate the superior fault classification efficacy of the proposed method. © 2024 IEEE.

关键词： Multipurpose robots

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Robust Reward Placement under Uncertainty 33

Robust Reward Placement under Uncertainty

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33rd international Joint conference on Artificial intelligence (IJCAI)

作者： Petsinis, Petros Zhang, Kaichen Pavlogiannis, Andreas Zhou, Jingbo Karras, Panagiotis Aarhus Univ Dept Comp Sci Aarhus Denmark Hong Kong Univ Sci & Technol Guangzhou Artificial Intelligence Thrust Guangzhou Peoples R China Baidu Res Business Intelligence Lab Beijing Peoples R China Univ Copenhagen Dept Comp Sci Copenhagen Denmark

ISBN: (纸本)9781956792041

We consider a problem of placing generators of rewards to be collected by randomly moving agents in a network. In many settings, the precise mobility pattern may be one of several possible, based on parameters outside our control, such as weather conditions. The placement should be robust to this uncertainty, to gain a competent total reward across possible networks. To study such scenarios, we introduce the Robust Reward Placement problem (RRP). Agents move randomly by a Markovian Mobility Model with a predetermined set of locations whose connectivity is chosen adversarially from a known set. of candidates. We aim to select a set of reward states within a budget that maximizes the minimum ratio, among all candidates in., of the collected total reward over the optimal collectable reward under the same candidate. We prove that RRP is NP-hard and inapproximable, and develop Psi-Saturate, a pseudo-polynomial time algorithm that achieves an is an element of-additive approximation by exceeding the budget constraint by a factor that scales as O(ln |Iota Iota|/is an element of). In addition, we present several heuristics, most prominently one inspired by a dynamic programming algorithm for the maxmin 0-1 KNAPSACK problem. We corroborate our theoretical analysis with an experimental evaluation on synthetic and real data.

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analysis of Automation in Foundries for Transforming Production Efficiency, Quality Control, and Operational Resilience 2

Analysis of Automation in Foundries for Transforming Product...

引用

2nd international conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Bhagyanathan, C. Sarvesh, J. Vishal, G. Rithvik, R. Sri Ramakrishna Engineering College Department of Mechanical Engineering Coimbatore India Sri Ramakrishna Engineering College Department of Robotics and Automation Coimbatore India

ISBN: (数字)9798331505745

ISBN: (纸本)9798331505745

The foundry industry, a cornerstone of manufacturing, has undergone significant transformations due to the integration of automation technologies. This survey paper examines the evolution of automation in foundries, exploring its historical development, key adoption drivers, and the ongoing challenges faced by traditional operations. Technological advancements driving this change include the Industrial Internet of Things (IIoT), robotics, artificial intelligence (AI), machine learning (ML), and cyber-physical systems (CPS), such as digital twins. Through case studies, the paper illustrates practical implementations of these technologies, such as IoT-enabled monitoring, robotics in core making and molding, AI-driven defect detection, and CPS integration in smart foundries. The advantages of automation are emphasized, including increased productivity, improved quality control, energy efficiency, sustainability, and enhanced workplace safety. Despite these benefits, the adoption of automation faces significant hurdles, such as high initial investment costs, integration with legacy systems, skill gaps, and cybersecurity concerns. The paper also identifies future trends, including the rise of collaborative robotics (cobots), edge computing, 5G technologies, and the vision for fully autonomous foundries. This comprehensive survey offers valuable insights into the current state of foundry automation, its transformative potential, and future directions for researchers and industry stakeholders seeking to leverage these advancements for operational excellence. © 2025 IEEE.

关键词： Coremaking

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Experimental Study on Validation of Typical Human Machine Interaction Tasks Based on GOMS Modified Model 5

Experimental Study on Validation of Typical Human Machine In...

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5th international conference on robotics, Intelligent Control and Artificial intelligence, RICAI 2023

作者： Shi, Jin-Shou Li, Lin-Jie Chen, Nan Ma, Chao Li, Yaping Beijing Polytechnic Beijing China

ISBN: (纸本)9798350357950

On the basis of improving the basic model through experiments in the early stage and obtaining a modified GOMS model, in order to verify its effectiveness, this article adopts an experimental method based on typical human-machine interaction tasks in complex information systems, combining Analytic Hierarchy Process with GOMS model analysis. Based on task analysis, typical human-machine interaction task experiments are carried out, Verify the task analysis of the model by comparing human task execution time with the task execution time predicted by GOMS task analysis theory through experiments. The experimental data results show that the error between GOMS predicted time and actual time is between 0.31% -14.02%, which is relatively close and can be used for human-machine interaction task analysis, usability design and evaluation of information systems. © 2023 IEEE.

关键词： experimental comparison GOMS model human-computer interaction task analysis

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