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共 4313 条记录，以下是261-270 订阅

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Efficiency Assessment of an Institute Through Parallel Network Data Envelopment Analysis 11th

Efficiency Assessment of an Institute Through Parallel Netwo...

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11th International Conference on Soft computing for Problem Solving, SocProS 2022

作者： Kumar, Atul Panwar, Ankita Pant, Millie Department of Applied Mathematics and Scientific Computing Indian Institute of Technology Roorkee Roorkee247667 India Mehta Family School of Data Science and Artificial Intelligence Indian Institute of Technology Roorkee Roorkee247667 India

ISBN: (纸本)9789811965241

Conventional data envelopment analysis (DEA) is a non-parametric approach to examine the efficiency of similar decision-making units (DMUs) as a whole system without considering its internal structure, i.e., the system is considered as a black box. Therefore, a network DEA (NDEA) is needed to study the internal structure of a system. By allowing for the measurement of individual components, an NDEA model can reveal inefficiencies that a traditional DEA ignores. In this study, we use the parallel network DEA to calculate the efficiency of a higher education institute with 19 decision-making units (DMUs) using two parallel processes (teaching and research) and compare it with the conventional DEA, CCR model through a numerical example. The main advantages of the parallel NDEA model are (i) to identify which DMUs are inefficient and make necessary adjustments, and (ii) the parallel DEA model has a lower efficiency score than the traditional DEA model. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Efficiency

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A Mathematical Model to Minimize the Total Cultivation Cost of Sugarcane 11th

A Mathematical Model to Minimize the Total Cultivation Cost ...

引用

11th International Conference on Soft computing for Problem Solving, SocProS 2022

作者： Kumar, Sumit Pant, Millie Department of Applied Mathematics and Scientific Computing Indian Institute of Technology Roorkee Uttarakhand Roorkee India Mehta Family School for Data Science and Artificial Intelligence Indian Institute of Technology Roorkee Uttarakhand Roorkee India

ISBN: (纸本)9789811965241

In the present study, a non-linear mathematical model is proposed to minimize the total expenditure made on sugarcane cultivation. The objective here is to optimize the costs involved in transportation, cultivation, and management of the deterioration of sugarcane. The optimization tools used are Differential Evolution (DE) and Particle Swarm Optimization (PSO). Further, the model is validated by comparing the actual expenditure of sugarcane cultivation with results obtained by PSO and DE, which indicates that the application of optimization methods may help in reducing the expenditure made on sugarcane cultivation. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deterioration

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Integrated Machine Learning Paradigms with Simulation based Mathematical Modeling for Dengue Fever

Integrated Machine Learning Paradigms with Simulation based ...

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Social and Sustainable Innovations in technology and Engineering (SASI-ITE), International Conference on

作者： S Dheva Rajan College of Computing and Information Sciences University of Technology and Applied Sciences Al Musannah Oman

ISBN: (数字)9798350360790

ISBN: (纸本)9798350360806

This investigation explores the creation and examination of a thorough mathematical model for the dynamics of dengue disease transmission, which includes important epidemiological variables and the dynamics of vaccination. The study investigates the usefulness of the model in forecasting epidemics, evaluating immunization plans, and enhancing public health interventions. The answer entails a thorough examination of periodic orbits and fixed points to reveal probable chaotic behavior and attractors. The behavior of the model under different parameter values is investigated using bifurcation analysis, providing insights into important aspects affecting dengue dynamics. The study also discusses the model’s relevance in practical decision-making and highlights its usefulness in forecasting the dengue virus’s worldwide burden.

关键词： Technological innovation Epidemics Machine learning Predictive models Mathematical models Orbits Vaccines

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Smart Posture Monitoring and Predictive Health Classification for Bedridden Patients Using IoT and AI

Smart Posture Monitoring and Predictive Health Classificatio...

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Innovative Approaches in Smart Technologies (ISAS), International Symposium on

作者： Sunitha Cheriyan Sudha Sakthivel Thirupathi Regula Kiran Kumar Said Al Riyami Department of IT College of Computing and Information Sciences University of Technology and Applied Sciences Muscat Oman

ISBN: (数字)9798331540104

ISBN: (纸本)9798331540111

Posture monitoring has emerged as a critical area of research and application, particularly considering increasing concerns about musculoskeletal disorders and their association with prolonged sitting and poor ergonomic practices. This study investigates the importance of posture monitoring and classification using a comprehensive dataset that includes demographic, and physiological, variables such as age, height, activity level, pain indicators, and personality traits. A pressure mapping system was used to gather data and various AI algorithms were applied to classify in-bed posture using the mined features of the dataset. With different in-bed postures, the study reached high classification accuracy. The performance of these algorithms was then evaluated with machine learning algorithms on the posture dataset. A dataset for posture monitoring and classification study is introduced for accurate and reliable monitoring and classification of these modern health and well-being issues. Relations between features and posture types are identified through the analysis and preprocessing of the dataset. We implemented the classification model using machine learning algorithms and evaluated the model performance evaluation using standard metrics like accuracy, precision, recall, and F1 Score. This paper details current posture assessment methods, providing an overview as well as a background for postural health management and ergonomic solutions. This study aims to propose an implementable posture classification model for a comprehensive assessment of body posture that may help bedridden patients have better health control and a better quality of life. This work might provide more effective care strategies to minimize the risks related to immobility. To achieve, both real-time monitoring and proactive health management, a smart classification monitoring system employs machine learning and Internet of Things technology to automatically identify, classify, and provide actionab

关键词： Machine learning algorithms Accuracy Ergonomics Machine learning Transforms Real-time systems Classification algorithms Monitoring Standards Testing

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Developing Innovative AI-Based Educational Guidance Systems to Meet the Needs of Each Student Individually: A Comprehensive Review

Developing Innovative AI-Based Educational Guidance Systems ...

引用

computing and Data Analytics (ICCDA), International Conference on

作者： Nasim Salim Ziyad Al Balushi College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Sultanate of Oman

ISBN: (数字)9798331542573

ISBN: (纸本)9798331542580

The influence of advanced technologies, especially artificial intelligence (AI), on the higher education sector is considerable and cannot be overlooked. It has been found out that this technology is beneficial both for tutors and students during the process of teaching and learning respectively. The primary issue that needs to be dealt with is the lack of personalized educational recommendations that would suit the specific needs, the modes of learning and the level of achievement of each particular learner. In most cases, academic institutions of a classical type offer standardized methods, which may, however, result to some students lagging behind or failing to cope with their study problems. The aimis to develop innovative systems for educational assistance based on AI technologies to solve particular issues like diversity in learning strategies and pace among learners and to ensure that a range of approaches are employed to elevate their learning experience. The system must adapt the teaching and the materials used, to the preferred way and rate of the student. In this particular research, a qualitative approach was adopted to engage in an extensive literature review of the broad field of educational psychology, adaptive learning systems, educational AI, and learning personalization. Examine the research and technological gaps which are the foundation of the proposed system. The results presented in this research show that it is necessary to improve the learning outcomes, the efficiency of resource usage and increase the level of engagement.

关键词： Ethics Data analysis Education Psychology Data protection Collaboration Learning (artificial intelligence) Artificial intelligence Research and development Systematic literature review

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Polish-ASTE: Aspect-Sentiment Triplet Extraction Datasets for Polish 30

Polish-ASTE: Aspect-Sentiment Triplet Extraction Datasets fo...

引用

Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Lango, Marta Naglik, Borys Lango, Mateusz Naglik, Iwo Poznan University of Technology Faculty of Computing and Telecommunications Poland Adam Mickiewicz University Faculty of Mathematics and Computer Science Poland Charles University Faculty of Mathematics and Physics Institute of Formal and Applied Linguistics Czech Republic

ISBN: (纸本)9782493814104

Aspect-Sentiment Triplet Extraction (ASTE) is one of the most challenging and complex tasks in sentiment analysis. It concerns the construction of triplets that contain an aspect, its associated sentiment polarity, and an opinion phrase that serves as a rationale for the assigned polarity. Despite the growing popularity of the task and the many machine learning methods being proposed to address it, the number of datasets for ASTE is very limited. In particular, no dataset is available for any of the Slavic languages. In this paper, we present two new datasets for ASTE containing customer opinions about hotels and purchased products expressed in Polish. We also perform experiments with two ASTE techniques combined with two large language models for Polish to investigate their performance and the difficulty of the assembled datasets. The new datasets are available under a permissive licence and have the same file format as the English datasets, facilitating their use in future research. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Extraction

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Spider Inspired Hexapod Mobile Robot With Ultrasonic SLAM Exploration In Hazards Environment

Spider Inspired Hexapod Mobile Robot With Ultrasonic SLAM Ex...

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Advances in technology and computing (ICATC), International Conference on

作者： Thisal Induwara Thisara Pathirana Thushani Mallikarathne Department of Applied Computing Faculty of Computing and Technology University of Kelaniya Kelaniya Sri Lanka Department of Mechanical and Manufacturing Faculty of Technology Wayamba University of Sri Lanka

ISBN: (数字)9798331518219

ISBN: (纸本)9798331518226

This research starts with issues of human operations in hazardous environments and the need for robots capable of handling such issues, then introduces the main concept a six legged robot, inspired by the biological structure and movement of spiders, designed and fabricated using 3d printing technology. This research is focused on the development and evaluation of a bio inspired hexapod mobile robot for mapping and exploration in hazardous environments. It incorporates slam technology, with a view to creating an accurate map in complex and hazardous terrains using the hector slam mapping tool. The results obtained show that the walking speed of the robot on flat surfaces is 4.8 cm/s and on uneven terrains, it walks at a speed of 4.2 cm/s with mapping accuracy of about 83%. Additionally, the robot's stability was confirmed through torque tests, showing that the motors could handle the required load, maintaining balance even under additional weight. This study concludes that the spider inspired hexapod robot is a viable solution for autonomous exploration in hazardous environments, offering significant potential for applications in search and rescue operations, disaster recovery, and inspection of dangerous sites. The study concludes that the spider inspired robot is a promising solution for navigating and mapping hazardous environments, with potential applications in disaster management and exploration.

关键词： Legged locomotion Simultaneous localization and mapping Accuracy Torque Navigation Inspection Three-dimensional printing Motors Hazards Acoustics

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'User AR' - Leveraging AI Based Augmented Reality for User Manuals 15

'User AR' - Leveraging AI Based Augmented Reality for User M...

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15th International Conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Shanmugam, Thirumurugan Chandrashekar, Chirag Bhati, Vipin Subburaj, Maheswari Sivaraman, Arun Kumar Sultana, Ajmery University of Technology and Applied Sciences College of Computing and Information Sciences Suhar Oman Vellore Institute of Technology School of Computer Science and Engineering Chennai India Photon Interactive Inc Digital Engineering Solution Center TorontoON Canada Algoma University School of Computer Science and Technology BramptonON Canada

ISBN: (纸本)9798350370249

The objective of this research is to propose an AI based novel augmented reality (AR) software to assist users in operating a wide range of technical and non-technical devices. The project's aim is to make this AR application, which provides detailed explanations of all the device's functions, more widely used than traditional user manuals. Augmented reality, which overlays digital information onto the real world, can be employed to develop an AR-based user manual for products or devices. Mobile applications that use a camera to recognize a product or device and display dynamic graphics, such as 3 D models, animations, or text, are one example of AR user manuals. These augmented reality user manuals enable consumers to quickly and easily learn how to operate, assemble, repair, or troubleshoot their purchased products. Experiments show that the proposed algorithm was able to recognize the object accurately with a percentage of 95.2%. © 2024 IEEE.

关键词： Artificial Intelligence Augmented reality (AR) Object Recognition

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Location Anonymous Query Algorithm based on Road Networks

Location Anonymous Query Algorithm based on Road Networks

引用

2022 International Conference on Augmented Intelligence and Sustainable Systems, ICAISS 2022

作者： Haohua, Qing Ibrahim, Roliana Nies, Hui Wen Universiti Teknologi Malaysia Faculty of Computing Department of Applied Computing and Artificial Intelligence Johor81310 Malaysia Guangzhou College of Technology and Business Guangdong Guangzhou510850 China

ISBN: (纸本)9781665489621

In this paper, we study the location anonymous query algorithm based on the Voronoi graph division of the road networks. The Voronoi diagram spatial analysis model has unique functions and application potential in the description of the location problems, the spatial partitioning of the landmarks based on the Voronoi diagram, on the one hand, it achieves the division of the spatial extent covered by the POI under the principle of shortest distance, and on the other hand, it also deals with the problem of the spatial partitioning. Hence, we propose the novel ideas of improving the division performance and also the query algorithm enhancement. Through the simulation, we select the Foshan city data as the target to evaluate the proposed model. © 2022 IEEE.

关键词： Location

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Classification of Attention Performance Post-Longitudinal tDCS via Functional Connectivity and Machine Learning Methods 9

Classification of Attention Performance Post-Longitudinal tD...

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9th IEEE International Conference for Convergence in technology, I2CT 2024

作者： Rao, Akash K. Menon, Vishnu K. Bhavsar, Arnav Chowdhury, Shubhajit Roy Negi, Ramsingh Dutt, Varun Indian Institute of Technology Mandi Applied Cognitive Science Laboratory Mandi India Indian Institute of Technology Mandi School of Computing And Electrical Engineering Mandi India Institute of Nuclear Medicine And Allied Sciences Cognitive Control And Machine Learning Group Delhi India

ISBN: (纸本)9798350394474

Attention is the brain's mechanism for selectively processing specific stimuli while filtering out irrelevant information. Characterizing changes in attention following long-term interventions (such as transcranial direct current stimulation (tDCS)) has seldom been emphasized in the literature. To classify attention performance post-tDCS, this study uses functional connectivity and machine learning algorithms. Fifty individuals were split into experimental and control conditions. On Day 1, EEG data was obtained as subjects executed an attention task. From Day 2 through Day 8, the experimental group was administered 1mA tDCS, while the control group received sham tDCS. On Day 10, subjects repeated the task mentioned on Day 1. Functional connectivity metrics were used to classify attention performance using various machine learning methods. Results revealed that combining the Adaboost model and recursive feature elimination yielded a classification accuracy of 91.84%. We discuss the implications of our results in developing neurofeedback frameworks to assess attention. © 2024 IEEE.

关键词： Electroencephalography

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