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2024 International Conference on Knowledge Engineering and Communication systems, ICKECS 2024

作者： Raman, Ramakrishnan Kumar, Vikram Pillai, Biju G. Rabadiya, Dhaval Patre, Smruti Meenakshi, R. India SRV Media Pvt. Ltd. India Faculty of Management It & Business Analytics India Parul Institute of Technology Parul University Computer Science and Engineering Faculty of Engineering and Technology India India Chennai Institute of Technology Computer Science and Engineering India

ISBN: (纸本)9798350359688

In the rapidly evolving field of computer vision and machine learning, recognizing human facial expressions with high accuracy remains a pivotal challenge. This paper introduces a novel Multi-Modal Facial Expression Recognition (MMFER) framework, leveraging a Hierarchical Cross-Attention Graph Convolutional Network (HCA-GCN) to enhance the accuracy and robustness of facial expression recognition. Our proposed HCA-GCN model systematically integrates multi-modal data sources, including visual imagery and depth information, to capture the complex and subtle nuances of human facial expressions. The hierarchical structure of our model allows for the efficient processing of multi-modal data through distinct pathways, ensuring that relevant features from each modality are effectively extracted and combined. The cross-attention mechanism within our framework meticulously aligns and emphasizes inter-modal features, fostering a synergistic integration that boosts the model's ability to discern intricate facial expressions. Through extensive experiments on benchmark datasets, our approach demonstrates significant improvements over existing methods, showcasing superior performance in recognizing a wide range of facial expressions under various conditions. The implementation details, including algorithms and mathematical expressions, are meticulously described to facilitate replication and further research. Results and discussions highlight the model's efficacy, underscored by comparative analysis and visualizations. Our findings indicate that the HCA-GCN model not only advances the state-of-the-art in facial expression recognition but also opens new avenues for research in multi-modal learning. © 2024 IEEE.

关键词： Spatio-temporal data

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Optimizing Routes for Improved Quality of Service in Wireless Sensor Networks through an Energy-Aware Routing Protocol for Maximizing Lifetime

Optimizing Routes for Improved Quality of Service in Wireles...

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2024 International Conference on Knowledge Engineering and Communication systems, ICKECS 2024

作者： Raman, Ramakrishnan Kumar, Vikram Pillai, Biju G. Rabadiya, Dhaval Patre, Smruti Meenakshi, R. India SRV Media Pvt. Ltd. India Biib Faculty of Management It & Business Analytics India Parul Institute of Technology Parul University Computer Science and Engineering Faculty of Engineering and Technology India Symbiosis Institute of Business Management Nagpur India Chennai Institute of Technology Computer Science and Engineering India

ISBN: (纸本)9798350359688

In the realm of Wireless Sensor Networks (WSNs), optimizing the Quality of Service (QoS) while ensuring the longevity of network operations remains a pivotal challenge, primarily due to the constrained energy resources of sensor nodes. This paper introduces a novel energy-aware routing protocol designed to enhance the QoS by optimizing routes within WSNs, thereby maximizing the network's operational lifetime. The proposed protocol employs a dual-focused approach, integrating energy efficiency with QoS parameters to select the most optimal routing paths. Through the deployment of a specialized routing algorithm alongside a comprehensive energy consumption model, the protocol strategically balances energy expenditure across the network, ensuring an equitable distribution of the energy load among sensor nodes. This methodology not only prolongs the operational lifespan of the network but also significantly improves the reliability and efficiency of data transmission. The efficacy of the proposed protocol is rigorously evaluated through a series of simulations, which demonstrate a marked improvement in both network lifetime and QoS, as compared to conventional routing protocols. The findings underscore the potential of integrating energy-aware considerations into routing decisions as a means to sustainably manage the critical resources of WSNs, thereby facilitating their broader application across various domains. © 2024 IEEE.

关键词： Sensor nodes

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Customer Segmentation Using Hierarchical Clustering 9

Customer Segmentation Using Hierarchical Clustering

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

作者： Afzal, Areeba Khan, Laiba Hussain, Muhammad Zunnurain Zulkifl Hasan, Muhammad Mustafa, Muzzamil Khalid, Aqsa Awan, Rimsha Ashraf, Farhan Khan, Zohaib Ahmed Javaid, Arslan Information Technology University Lahore Department of Computer Engineering Punjab Pakistan Bahria University Lahore Campus Dept. of Computer Science Pakistan University of Central Punjab Lahore Faculty of Information Technology Department of Computer Science Pakistan National College of Business Administration And Economics Department of Computer Science Lahore Pakistan Information Technology University Lahore Pakistan

ISBN: (纸本)9798350394474

In the dynamic landscape of retail, understanding customer behavior is paramount for businesses seeking to optimize marketing strategies and enhance the shopping experience. This study explores the utilization of hierarchical clustering techniques for mall customer segmentation, with a focus on the paper titled 'MALL CUSTOMER SEGMENTATION USING MACHINE LEARNING' as the benchmark. Our dataset encompasses a diverse range of mall customers, spanning demographics and behavioral attributes. Hierarchical clustering systematically groups customers into clusters, revealing distinct segments within the mall's customer base. A comprehensive analysis of these clusters unveils profound insights into customer tendencies, preferences, and purchasing habits. These insights form a solid foundation for tailored marketing campaigns, personalized recommendations, and resource allocation within the mall. The study contributes significantly to customer analytics, providing retailers with a powerful tool to gain a competitive edge in the retail sector. By leveraging hierarchical clustering for mall customer segmentation, businesses can enhance customer satisfaction, drive sales, and foster lasting customer relationships. This paper underscores the importance of data-driven methodologies in understanding customer behavior and offers a practical framework for businesses to harness the potential of hierarchical clustering for strategic decision-making in the retail industry. © 2024 IEEE.

关键词： Consumer behavior

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When Left Behind in Multi-User Virtual Reality: Clues to Indicate the Absence of Users

When Left Behind in Multi-User Virtual Reality: Clues to Ind...

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2022 International Conference on Cyberworlds, CW 2022

作者： Wolfel, Matthias Basing, Lara-Marie Deuchler, Jonas Karlsruhe University of Applied Sciences Faculty of Computer Science and Business Information Systems Germany University of Hohenheim Faculty of Business Economics and Social Sciences Germany

ISBN: (数字)9781665468145

ISBN: (纸本)9781665468145

Recently, with the increasing popularity of immersive virtual reality, synchronous communication via avatars in virtual worlds has become more popular. In contrast to asynchronous communication - like social media platforms - people expect others to be present during embodied, virtual interactions. However, for a variety of reasons, this is not always the *** some communication media provide a good indicator that the other is still present, such as live images of the conversation partner in video conferencing, not all media do provide this information naturally, e.g., when the interlocutor is silent on the phone. In immersive multi-user virtual reality, a wrong and misleading signal may even be provided when an avatar is still shown while its owner is absent. In many situations, an assumed presence of the other who is actually no longer there can lead to confusion. In the presented empirical study, we show that users in shared immersive environments prefer an indicator when a person is absent and that the preferred way of visualization depends on the use case. © 2022 IEEE.

关键词： Virtual reality

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A Well Structured Design for Individualized Healthcare System via Fuzzy Logic System (FLS) 4

A Well Structured Design for Individualized Healthcare Syste...

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4th IEEE International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2024

作者： Raman, Ramakrishnan Verma, Apurv Kumar, Vikram Rastogi, Shailesh Pillai, Biju G. Meenakshi, R. India Parul Institute of Technology Parul University Computer Science and Engineering Faculty of Engineering and Technology India Srv Media Pvt. Ltd India Pune India Faculty of Management It & Business Analytics India Institute of Technology Computer Science and Engineering Chennai India

ISBN: (纸本)9798350360165

Personalized medicine is driving the need for new and customized biopharmaceuticals using proteins that have been changed. As such, it is critical to evaluate these items for allergenicity before introducing them as treatments. Even though there are a number of techniques available to predict the allergenicity of proteins, it may still be difficult to discriminate between allergens and nonallergens, particularly when the allergens have a considerable sequence resemblance to their known counterparts. To address this, we provide 'FuzzyApp,' a novel fuzzy rule-based system that evaluates a query protein's potential for allergenicity. FuzzyApp uses fuzzy IF-THEN rules that come from five different modules to determine how allergenic a protein is. FuzzyApp outperforms the state-of-the-art techniques on a variety of datasets, attaining a pleasing trade-off between specificity and sensitivity, as shown by an upbeat Mathew's correlate coefficient. FuzzyApp's capacity to distinguish allergens from allergen-like potential nonallergens (APN) is highlighted by its notable high specificity in this regard. The efficacy and uniformity of this suggested approach are further supported by error analysis and analysis of the whole proteome dataset. Furthermore, Tropomyosin from a variety of allergic and nonallergenic sources is properly predicted by FuzzyApp. The companion online service helps users comprehend the reasoning behind predictions by facilitating batch sequence filing and presenting findings in coherent words. © 2024 IEEE.

关键词： Personalized medicine

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A Parallel Hybrid Testing Technique for Tri-Programming Model-Based Software systems

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computers, Materials & Continua 2023年第2期74卷 4501-4530页

作者： Huda Basloom Mohamed Dahab Abdullah Saad AL-Ghamdi Fathy Eassa Ahmed Mohammed Alghamdi Seif Haridi Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddah21493Saudi Arabia KTH Royal Institute of Technology StockholmSweden

Recently,researchers have shown increasing interest in combining more than one programming model into systems running on high performance computing systems(HPCs)to achieve exascale by applying parallelism at multiple *** different programming paradigms,such as Message Passing Interface(MPI),Open Multiple Processing(OpenMP),and Open Accelerators(OpenACC),can increase computation speed and improve *** the integration of multiple models,the probability of runtime errors increases,making their detection difficult,especially in the absence of testing techniques that can detect these *** studies have been conducted to identify these errors,but no technique exists for detecting errors in three-level programming *** the increasing research that integrates the three programming models,MPI,OpenMP,and OpenACC,a testing technology to detect runtime errors,such as deadlocks and race conditions,which can arise from this integration has not been ***,this paper begins with a definition and explanation of runtime errors that result fromintegrating the three programming models that compilers cannot *** the first time,this paper presents a classification of operational errors that can result from the integration of the three *** paper also proposes a parallel hybrid testing technique for detecting runtime errors in systems built in the C++programming language that uses the triple programming models MPI,OpenMP,and *** hybrid technology combines static technology and dynamic technology,given that some errors can be detected using static techniques,whereas others can be detected using dynamic *** hybrid technique can detect more errors because it combines two distinct *** proposed static technology detects a wide range of error types in less time,whereas a portion of the potential errors that may or may not occur depending on the 4502 CMC,2023,vol.74,no.2 operating environme

关键词： Software testing hybrid testing technique OpenACC OpenMP MPI tri-programming model exascale computing

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A Metamodel for a DSL to Design Decision Support systems in Smart Tourism

A Metamodel for a DSL to Design Decision Support Systems in ...

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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Ouaddi, Charaf Benaddi, Lamya Souha, Adnane Naimi, Lahbib Bouziane, El Mahi Jakimi, Abdeslam Moulay Ismail University Software Engineering and Information Systems Engineering Team Faculty of Science and Technology Errachidia Department of Computer Sciences Morocco

ISBN: (纸本)9798350369106

The development of Decision Support systems (DSS) for several companies operating in sectors such as tourism, healthcare, or others, presents significant challenges due to the nature of their multi-component architecture. A typical DSS consists of a data component, a model component incorporating machine learning and deep learning techniques, and a user interface component, each one requires diverse technologies. This complexity increases development time and effort, hindering the efficient design of DSS tailored to specific domains like tourism, where real-time decision-making is essential. One promising approach to overcome these challenges is the use of Domain-Specific Languages (DSLs). DSLs allow developers to model and generate code more efficiently by providing high-level abstractions suited to the domain. By leveraging DSLs, it is possible to simplify the design process and automate the generation of code or parts of the DSS, thereby reducing the overall complexity and time required for development. This paper proposes a metamodel for designing DSS, specifically for the Smart Tourism sector. The metamodel serves as a foundation for the creation of DSL. The goal is to provide a solution to facilitate the development of DSS for the demands of tourism. The paper outlines the key concepts, approach, and results, presenting the first element of the proposed DSL which is the metamodel capturing the essential components and relationships for DSS in Smart Tourism. © 2024 IEEE.

关键词： Digital subscriber lines

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The Relationship Between Nomophobia, Emotional Intelligence, Interpersonal Problem-Solving, Perceived Stress, and Self-esteem Among Undergraduate Students

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Journal of Technology in Behavioral science 2023年第1期8卷 27-35页

作者： Karaoglan Yilmaz, Fatma Gizem Yilmaz, Ramazan Erdogdu, Fatih Faculty of Science Department of Computer Technology & Information Systems Bartin University Bartin Turkey Department of Computer Technologies Ereğli Vocational School Bulent Ecevit University Zonguldak Turkey

Nomophobia is derived from “no mobile phobia”;it is defined as the fear of being away from the possibility of communication by mobile phone. Since mobile phones are used actively in many fields, from communication to social media, from the stock market to e-commerce, users can practically follow developments in their areas of interest with their mobile phones. This situation reveals the need for users to keep their phones with them all the time and can trigger the development of nomophobia feelings. This fear can become increasingly common among mobile phone users today and may require clinical interventions due to its consequences. Researchers state that the investigation of factors that cause nomophobia can inform subsequent interventions and guidance studies to overcome this fear. Various studies have been carried out to determine the causes of nomophobia. In these studies, the importance of individual psycho-social factors is revealed. However, it is emphasized that dimensions related to psycho-social factors need to be explored. One of them is the relationship of nomophobia with emotional intelligence, interpersonal problem-solving, perceived stress, and self-esteem. This study investigated the structural relationships between university students’ nomophobia and emotional intelligence, interpersonal problem-solving, perceived stress, and self-esteem. The research was carried out on 543 university students. Fifty-seven percent of the students participating in the study were female, and 43% were male. Path analysis was performed in the analysis of the data. The results of the research reveal that as the interpersonal problem-solving skills of university students improve, nomophobia decreases. Depending on the development of emotional intelligence, students’ interpersonal problem-solving skills increase. In addition, the development of emotional intelligence reduces the level of perceived stress. In line with the findings obtained from the research, various sugges

关键词： Emotional intelligence Interpersonal problem-solving Nomophobia Perceived stress Self-esteem Undergraduate students

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Calligraphy Alphabet Perception Using Artificial Intelligence 9

Calligraphy Alphabet Perception Using Artificial Intelligenc...

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9th International Conference on science, Technology, Engineering and Mathematics, ICONSTEM 2024

作者： Venkatesh, S. Jeevitha, D. Gnanaselvi, J. Anitha Srm Institute of Science And Technology Department of Data Science And Business Systems School of Computing Chennai Kattankulathur India Jeppiaar Engineering College Department of Computer Science And Engineering Chennai India

ISBN: (纸本)9798350365092

The human brain has a simple time analyzing and processing images. The brain is able to rapidly deconstruct and distinguish an image's various components when the eye perceives it. With the Convolutional Neural Network (CNN) as its foundation, this research suggests deep learning conceptual models. When the algorithms are compared, it becomes clear that CNN-based classification of handwritten alphabets performs better than other algorithms in terms of accuracy. The Manual Net, Alex Net, and LeNet Architectures are among the CNN algorithms employed in this research. The convulational layer, max pooling, flattening, feature assortment, rectifier lined unit, and completely linked softmaxx layers are each components of the aforementioned designs. The proposed network is tested using an image dataset comprising 530 training photos and 2756 testing images. The top precision and cost-efficient model will be used in the Django context to build a handler line for supplying the appeal to be recognized and obtaining the productivity outcome of recognized appeal. © 2024 IEEE.

关键词： Convolutional neural networks

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Enhancing Telemarketing Success Using Ensemble-Based Online Machine Learning

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Big Data Mining and Analytics 2024年第2期7卷 294-314页

作者： Shahriar Kaisar Md Mamunur Rashid Abdullahi Chowdhury Sakib Shahriar Shafin Joarder Kamruzzaman Abebe Diro Department of Information Systems and Business Analytics RMIT UniversityMelbourne 3000Australia School of Engineering and Technology Central Queensland UniversityRockhampton 4700Australia Faculty of Engineering Computer and Mathematical ScienceUniversity of AdelaideAdelaide 5005Australia Centre for Smart Analytics Federation University AustraliaBallarat 3350Australia School of Accounting Information Systems and Supply ChainRMIT UniversityMelbourne 3000Australia

Telemarketing is a well-established marketing approach to offering products and services to prospective *** effectiveness of such an approach,however,is highly dependent on the selection of the appropriate consumer base,as reaching uninterested customers will induce annoyance and consume costly enterprise resources in vain while missing interested *** introduction of business intelligence and machine learning models can positively influence the decision-making process by predicting the potential customer base,and the existing literature in this direction shows promising ***,the selection of influential features and the construction of effective learning models for improved performance remain a ***,from the modelling perspective,the class imbalance nature of the training data,where samples with unsuccessful outcomes highly outnumber successful ones,further compounds the problem by creating biased and inaccurate ***,customer preferences are likely to change over time due to various reasons,and/or a fresh group of customers may be targeted for a new product or service,necessitating model retraining which is not addressed at all in existing works.A major challenge in model retraining is maintaining a balance between stability(retaining older knowledge)and plasticity(being receptive to new information).To address the above issues,this paper proposes an ensemble machine learning model with feature selection and oversampling techniques to identify potential customers more accurately.A novel online learning method is proposed for model retraining when new samples are available over *** newly introduced method equips the proposed approach to deal with dynamic data,leading to improved readiness of the proposed model for practical adoption,and is a highly useful addition to the *** experiments with real-world data show that the proposed approach achieves excellent results in all cases(e.g.,98.6

关键词： machine learning online learning oversampling telemarketing imbalanced dataset ensemble model

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