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Advertisement Recommendation System as a Fuzzy Knapsack Problem

Advertisement Recommendation System as a Fuzzy Knapsack Prob...

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Oner, Ceren Oztami, Bapr Istanbul Tech Univ Ind Engn Dept Istanbul Turkiye Huawei R&D Ctr Shenzhen Peoples R China

ISBN: (纸本)9783031671944;9783031671951

Effective advertisement allocation is a critical aspect within recommendation systems, necessitating robust methodologies such as the knapsack problem to accommodate a multitude of constraints. In our study, we delve into the intricacies of addressing the advertisement allocation problem through a fully fuzzy knapsack framework, aiming to provide comprehensive model insights. Our proposed methodology encompasses four key modules meticulously designed to preprocess data for the primary advertisement allocation model. These modules comprise: (i) the utilization of a Fuzzy Inference System (FIS) for detecting advertisement prices, (ii) the segmentation of locations employing Interval Valued Intuitionistic Fuzzy C Means (IVIFCM) clustering, (iii) the segmentation of users through Interval Valued Fuzzy Clustering (IVFC), and (iv) the integration of FastText to estimate the probability of sequential location visits. These modules serve as indispensable components of the fuzzy advertisement allocation problem, which we model as a fully fuzzy knapsack problem. Through our detailed exploration, we aim to offer valuable insights into the operationalization of advertisement allocation amidst imprecise data, thereby facilitating the decision-making process in advertisement display.

关键词： Fuzzy recommendation systems fuzzy knapsack problem

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E-learning and Augmented Reality: A Systematic Literature Review 4th

E-learning and Augmented Reality: A Systematic Literature Re...

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4th International Conference on Digital Technologies and Applications (ICDTA)

作者： Elamrani, Lobna Moughit, Mohamed Sultan Moulay Univ Res Team LASTI Lab Sci & Technol Engn Transmiss & Commun Informat Dept Khouribga Beni Mellal Morocco

ISBN: (纸本)9783031686528;9783031686535

This comprehensive systematic literature review delves into exploring how augmented reality (AR) technologies can significantly enhancethe e-learning landscape. The objective is to understand the multifaceted impact of AR integration and scrutinize the current state of research, prevalent theories, and practical applications within e-learning. The study examines the dynamic interplay between AR and e-learning, spanning prevalent research trends and theoretical frameworks. The review seeksto shed light on the tangible benefits that AR brings to the e-learning environment. The results of this investigation underscore the emergence of augmented reality as an up-and-coming and impactful tool in the domain of e-learning. One of its key strengths lies in its capacity to amplify learner engagement. The culmination of the review involves providing valuable recommendations for future research endeavors. These recommendations guide scholars and researchers in exploring new dimensions, addressing potential gaps, and advancing the understanding of AR's role in e-learning.

关键词： Augmented reality (AR) E-Learning Systematic Literature review

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On Some Common Centrifugal Pumps Natural Frequency Issues 10th

On Some Common Centrifugal Pumps Natural Frequency Issues

引用

International Conference on New Technologies, Development and Application - Advanced Production Processes and Intelligent systems

作者： Neziric, Emir Isic, Safet Dzemal Bijedic Univ Mostar Fac Mech Engn Mostar 88104 Bosnia & Herceg

ISBN: (纸本)9783031662676;9783031662683

Centrifugal pumps are unavoidable parts of hydraulic systems and they are used for transportation of different kinds of fluids from one place to another. Their condition could be monitored and determined by vibration measurements, where common faults are recognizable by standard vibrational characteristics. Natural frequencies of the pump-pedestal structure are unfairly neglected in the available literature. The finite element method is the common method for the pump impeller or the whole pump assembly natural frequency determination and it could be used the same for the pump-pedestal structure natural frequency determination. Two case studies of the natural frequency issues in the centrifugal pumps are shown in this paper. It is shown the importance of the modal analysis of the whole pump-pedestal structure during the design and assembly phase of pumping stations.

关键词： centrufugal pumps natural frequency vibration analysis

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Hardware Accelerators for Classification of Thoracic Disorders: A Survey 9th

Hardware Accelerators for Classification of Thoracic Disorde...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Sharma, Pawan Gurunarayanan, S. Karuppiah, Anupama Birla Inst Technol & Sci Pilani Pilani Campus Pilani India Birla Inst Technol & Sci Pilani Hyderabad Campus Hyderabad Telangana India Birla Inst Technol & Sci Pilani KK Birla Goa Campus Sancoale Goa India

ISBN: (纸本)9789819732982;9789819732999

Deep learning, specifically convolutional neural networks (CNNs), has been successfully applied to the classification of chest X-ray images for diagnosing thoracic diseases. CNNs are effective in learning intricate patterns and features from images by training on large, labeled datasets. With this training, they can identify specific patterns associated with different thoracic diseases and classify new, unseen chest X-ray images into relevant disease categories. This application of Deep Neural networks aids in the diagnosis and treatment of patients with thoracic diseases. The paper discusses the role of hardware accelerators, specifically Field-Programmable Gate Arrays (FPGAs), in accelerating deep learning model training processes. It emphasizes the importance of powerful hardware for deep learning advancements due to the need for vast amounts of data and high computing capabilities. The paper surveys techniques for implementing and optimizing convolutional neural networks (CNNs) on FPGA platforms, highlighting their efficiency and re-configurability. It also addresses the challenges in designing related embedded systems and proposes a complete acceleration design flow that explores different interfaces between the CPU and hardware accelerators.

关键词： FPGA GPU Deep learning CNN Chest X-ray Hardware accelerator

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Development of a Chatbot Prototype to Serve University Graduates in the Process of Obtaining Degrees and Professional Titles

Development of a Chatbot Prototype to Serve University Gradu...

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Intelligent systems Conference

作者： Apaza, Honorio Reynoso, Allison I. Balcona, Jamir E. Maquera, Seline M. Coaguila, Maribel E. Univ Nacl Moquegua Ilo Peru

ISBN: (纸本)9783031663352;9783031663369

This research proposes the development of a natural language processing (NLP) chatbot to accurately and efficiently answer questions from graduates of the Universidad Nacional de Moquegua (UNAM) about their degree and title requirements. The objective is to address the complexity and volume of university regulations that make it difficult for students to find accurate information, generating frustration and delays in the degree process. The chatbot will be trained with a corpus of questions and answers extracted from the regulations, allowing it to understand and respond to queries in natural language in a timely and accurate manner. This chatbot is expected to improve user experience, optimize administrative resources and increase accessibility to information. Established performance standards include accuracy, relevance, clarity, and ease of use. The chatbot differs from other approaches by its specific focus on degree and title requirements, using a corpus of questions and answers extracted from the UNAM regulations to ensure the accuracy and relevance of the information provided. This chatbot is expected to become a valuable tool for students and administrative staff at the university.

关键词： Chatbot NLP Question answer University graduates Process of obtaining degrees

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Shared Intentionality Before Birth: Emulating a Model of Mother-Fetus Communication for Developing Human-Machine systems 1

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Intelligent systems Conference (IntelliSys)

作者： Danilov, Igor Val Liepaja Univ Liepaja Latvia

ISBN: (数字)9783031477157

ISBN: (纸本)9783031477140;9783031477157

Numerous studies show the ability of fetuses for affective evaluation and sensitivity to the sounds and rhythms of other human presence. This shows an appearance of fetuses' perception in intentional engagement with the environment. It means that fetuses are able to select the relevant stimulus from the noisy environment with a cacophony of other stimuli: chemical interactions, pressure changes, and electromagnetic fields. This ability can appear in ecological learning only. The theoretical study observes the literature to understand what environmental features of the mother-fetus communication model enable a fetus to interact with the mother in ecological training. The objective is to design Human-Machine systems and, specifically, computer-aided Medical Diagnosis systems based on the mother-fetus communication model. The article proposes the physiological mechanism of shared intentionality that relies on the mother's heart pulsed electromagnetic field (PEMF) impact on the adenosine receptors in both organisms. The study creates the concept design for future research to provide evidence of the mother-fetus communication model and establish human-computer connectivity.

关键词： Communication model Human-machine systems Shared intentionality

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An Intuitive Study on the Variants of Watson Crick Automata Using Rough Sets

An Intuitive Study on the Variants of Watson Crick Automata ...

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International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Jansirani, N. Vijayaraghavan, N. Dare, V. R. Univ Madras Queen Marys Coll Chennai 600004 Tamil Nadu India KCG Coll Technol Chennai 600097 Tamil Nadu India Univ Madras Madras Christian Coll Chennai 600059 Tamil Nadu India

ISBN: (纸本)9783031671913;9783031671920

The Main aim of this research article is to study Watson Crick Automaton and Watson Crick Online Tessellation Automaton through Rough Transition Map. Rough set theory got introduced in Automata theory to find Rough Finite State Automaton. The idea of incorporating Rough sets with Watson Crick Automaton was done thereby introducing Watson Crick Rough Automaton. Here in this research paper, some of the properties of Watson Crick Rough Automaton are studied. The concept of Watson Crick Rough Online Tessellation Automaton is introduced and its corresponding Rough languages are discussed. Finally the Computational powers of the above variants of Watson crick Automata under Boolean operations are analyzed.

关键词： Double Stranded Array Rough Tessellation

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Hybrid CNN and RNN for Twitter Sentiment Analysis 8th

Hybrid CNN and RNN for Twitter Sentiment Analysis

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Pujari, Pratik Padalia, Adish Shah, Tanish Devadkar, Kailas Univ Mumbai Sardar Patel Inst Technol Dept Comp Engn Mumbai Maharashtra India Univ Mumbai Sardar Patel Inst Technol Dept Informat Technol Mumbai Maharashtra India

ISBN: (纸本)9789819713257;9789819713264

Online social media networks have developed into a widespread and significant platform for people to freely express their thoughts and emotions in this era of digital communication. This change in communication habits has important ramifications for brands looking to connect with and understand their target market. Social media is one of the biggest sources of unstructured data, but it takes time to analyze it and extract its meaning. This paper attempts to forecast sentimental analysis based on Twitter user's tweets. We used a Twitter dataset which contains around 520 k Tweets, to predict whether the tweet has a positive or a negative connotation which can further help us to understand the mental state of the user. Then, using this dataset, we develop different deep learning models (including RNN and CNN). We examine the outcomes of applying recurrent neural network (RNN) and convolutional neural network (CNN) to these models. Finally, we suggested an approach that combines RNN and CNN to fully exploit each technology's advantages: RNN can learn temporal and context features, notably long-term dependency between multiple entities, while CNN is capable of catching numerous potential features. The result demonstrates that our method is superior to the majority of the existing methods.

关键词： Sentiment analysis Deep learning Convolutional neural network (CNN) Recurrent neural network (RNN)

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A Survey on Conventional Multilevel Inverter Topologies 8th

A Survey on Conventional Multilevel Inverter Topologies

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Nagar, Ruchir Shroff, Kaushik Jagtap, Aarti Patil, Nitin B. Patil, Lalit P. SCTRs Pune Inst Comp Technol Pune Maharashtra India

ISBN: (纸本)9789819713257;9789819713264

Multilevel inverters have gained significant attention in recent years due to their ability to minimize switching losses, improve the quality of output voltage waveforms, and attenuate voltage harmonics. They have several advantages over the traditional two-level inverter. This research paper provides a thorough comparative analysis of various multilevel inverter topologies, highlighting their distinctive characteristics, advantages, and limitations. This study, uses simulations to systematically compare multilevel inverter topologies, including the Diode Clamped, Flying Capacitor, and Cascaded H-Bridge inverters based on various parameters. A quantitative comparison between these three standard topologies provides a basis for research being carried out in terms of modern topology propositions.

关键词： Multilevel inverter (MLI) Topologies Five-level inverter Total harmonic distortion (THD) Simulation Sinusoidal waveform

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Modeling of Models and Processes that Differentiate Semantically Polyfunctional Words in the Context of the Uzbek Language 9th

Modeling of Models and Processes that Differentiate Semantic...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Boltayevich, Elov Botir Tursunalievna, Abdurahmonova Muqaddas Ilxomovna, Axmedova Xolisxon Xolmo'minovna, Abdullayeva Oqila Farkhodovich, Kholmukhamedov Bakhtiyor Tashkent State Univ Tashkent Qituvchi St 103 Tashkent Uzbekistan Samarkand State Univ Samarqand Univ Xiyoboni 15 Samarkand Uzbekistan

ISBN: (纸本)9789819732982;9789819732999

Another urgent issue of applied linguistics is to create a linguistic filter for semantically distinguishing polyfunctional words, and for the field of computer linguistics, it is an urgent issue to develop mathematical models and algorithms for semantically distinguishing them, as well as an information system. This article discusses the models for semantic differentiation of polyfunctional words in the Uzbek language when they occur in the structure of a sentence. We got acquainted with studies of the Turkic language family. A hierarchy of polyfunctional words in the Uzbek language in terms of word groups has been formed. Mathematical models for semantically differentiating polyfunctional words within the categories noun. adjective, adjective. modal word, adjective. adverb, auxiliary verb. independent verb, and conclusion. auxiliary are presented. The business processes distinguishing the polyfunctionality of the Uzbek language semantic analyzer were modeled, and the conceptual model of the information system, its architecture, and structure were developed. The developed information system is based on the MVT architecture and was developed using the Python programming language. The efficiency of the developed mathematical models was 71.7%.

关键词： Polyfunctional words Mathematical model Set Finite set Business processes Modeling Vocabulary Conceptual model Structure and architecture of information system

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