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Interactive E-Commerce: Addressing Cart Abandonment through Gamified User Engagement

Interactive E-Commerce: Addressing Cart Abandonment through ...

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2024 International conference on Communication, Computing and Internet of Things, IC3IoT 2024

作者： Sohanda, Mayank Kumar Gupta, Mihir Kalpana, A.v. Srm Institute Of Science And Technology School Of Computing Department Of Data Science And Business Systems Kattankulathur India

ISBN: (纸本)9798350352689

This paper addresses the pervasive issue of cart abandonment in online shopping, a phenomenon that significantly impacts e-commerce revenue streams. Through an investigation into the underlying causes, we identify the lack of social engagement as a critical factor contributing to this behavior. Our primary objective is to bridge the gap between item selection and purchase completion by enhancing the user experience and boosting conversion rates. To tackle this challenge, we propose a novel approach by integrating gamification strategies into the online shopping experience. Our methods include implementing real-time user activity indicators, such as visual representations of active shoppers and interactive leaderboards, to foster a sense of community and competition among users. Additionally, we introduce social shopping features, such as cart sharing and real-time feedback systems, to promote user collaboration and interaction. Preliminary data analysis reveals a significant increase in conversion rates following the implementation of these gamification strategies. Users are more inclined to complete purchases within a community-centric and competitive environment. Moreover, the introduction of social elements has enriched the overall shopping experience, as evidenced by user feedback and heightened engagement on the platform. In conclusion, our study demonstrates the effectiveness of integrating gamification elements into online shopping platforms to combat cart abandonment. By creating a more engaging and communal shopping environment, users are not only motivated to complete purchases, but also to enjoy a more fulfilling shopping experience. Our findings highlight the potential of gamification as a powerful tool for enhancing e-commerce platforms and offer valuable insights for future advancements in online retail strategies. © 2024 IEEE.

关键词： Sales

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Improving Machine Translation with Human Feedback: An exploration of Quality Estimation as a Reward Model

Improving Machine Translation with Human Feedback: An Explor...

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2024 conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2024

作者： He, Zhiwei Wang, Xing Jiao, Wenxiang Zhang, Zhuosheng Wang, Rui Shi, Shuming Tu, Zhaopeng Shanghai Jiao Tong University China Tencent AI Lab China

ISBN: (纸本)9798891761148

Insufficient modeling of human preferences within the reward model is a major obstacle for leveraging human feedback to improve translation quality. Fortunately, quality estimation (QE), which predicts the quality of a given translation without reference, has achieved impressive alignment with human evaluations in the last two years. In this work, we investigate the potential of employing the QE model as the reward model to predict human preferences for feedback training. We first identify the overoptimization problem during QE-based feedback training, manifested as an increase in reward while translation quality declines. We examine the problem and argue that the vulnerability of the QE model might lead to high rewards for incorrect translations, resulting in overoptimization and error propagation. To address the problem, we adopt a simple yet effective method that uses heuristic rules to detect the incorrect translations and assigns a penalty term to the reward scores of them. Experimental results show that the proposed QE-based feedback training achieves consistent and significant improvements across various settings, further verified through human preference studies. Our subsequent analysis demonstrates the high data efficiency of the proposed QE-based feedback training: it outperforms systems using larger parallel corpora by a small amount of monolingual data. Our code is available at: https://***/zwhe99/FeedbackMT © 2024 Association for Computational Linguistics.

关键词： Quality control

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A Nonlinear Neuro-Cognitive exploration on the Timbre Dependence of Emotion 8

A Nonlinear Neuro-Cognitive Exploration on the Timbre Depend...

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8th IEEE International conference on Information and Communication Technology, CICT 2024

作者： Banerjee, Archi Sanyal, Shankha Sengupta, Ranjan Ghosh, Dipak Academy of Classical and Folk Arts Indian Institute of Technology Kharagpur Kharagpur India Sir C. V. Raman Centre for Physics and Music Jadavpur Universiy Kolkata India

ISBN: (纸本)9798331531539

Indian Classical Music (ICM) has been known to convey a variety of emotional responses among the listeners since time immemorial, but neural attributes of these emotional experiences are largely unexplored till date. One of our earlier studies based on acoustical time series analysis reported that the timbre of an instrument can play significant role in conveying different emotions through various raga clips. This study aims to explore the neuro-cognitive attributes of the same. Taking two-minute aalaap (opening) sections of six popular ragas (three of them are conventionally known to portray happiness and the rest three sadness) of ICM, played in three different musical instruments (sitar, sarod and flute) by three maestros of ICM, this study attempted to look for the neural cues for these two contrasting emotions and if (and how) the timbre of the instrument plays any significance in their perception. EEG data was recorded from 10 (8 male, 2 female) participants while they listened to these music clips and their brain responses for each clip were analyzed with nonlinear chaos-based MFDFA technique in a comparative manner in order to look for specific arousal activities in different lobes of the brain corresponding to the contrasting music-evoked emotions. Our findings revealed that the multifractal spectral width obtained from alpha/theta frequency ranges of EEG data can be developed as a parameter for the development of an automated emotion recognition system. This study may prove to have far reaching implications in the development of an automated emotion classifier algorithm in future. © 2024 IEEE.

关键词： Emotion Recognition

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Optimizing Medical Image Report Generation with varied Attention Mechanisms 6

Optimizing Medical Image Report Generation with Varied Atten...

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6th International conference on Contemporary Computing and Informatics, IC3I 2023

作者： Reddy, Pochamreddy Mukesh verma, vivek Kumar Chaitanya varma, Mudunuri venkata Manipal University Jaipur Computer and Communication Engineering Jaipur India Manipal University Jaipur Department of Information Technology Jaipur India Manipal University Jaipur Data Science and Engineering Jaipur India

ISBN: (纸本)9798350304480

Image captioning plays a crucial role in interpreting visual information in the medical field. This research paper represents an innovative approach to produce descriptive and insightful reports for its respective medical images. The combination of natural language processing and computer vision techniques are used, an encoder-decoder architecture is employed which aids in leveraging by using a qualified Inceptionv3 model to extract image features. The captions which are generated were based on a deep learning model with a Gated Recurrent Unit-based decoder and an attention mechanism, guaranteeing the connection between the generated text to the image content. The research focuses mainly on the dataset which consists of medical images with its associated reports by utilizing data extraction and preprocessing methods to enhance the accuracy and contextual understanding of the generated report. The experiments and results section demonstrate the implementation details and efficacy of the proposed model in generating meaningful report for the medical image, thereby facilitating enhanced interpretation and analysis of medical images. This research contributes to the advancement of image captioning techniques in the medical domain and holds significance for clinical decision support systems and medical image analysis. © 2023 IEEE.

关键词： computer vision Gated Recurrent Unit inception v3 natural language processing

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Literature Bibliometrics Atlas analysis of Experience Design 10th

Literature Bibliometrics Atlas Analysis of Experience Design

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10th International conference on Culture and Computing (C and C) Held as Part of the 24th International conference on Human-Computer Interaction (HCII)

作者： Wang, Yu Xin, Xiangyang Yu, Hao Cheng, Haolun Jin, Beiting Jiangnan Univ Sch Design Wuxi 214122 Jiangsu Peoples R China Beijing Inst Graph Commun Beijing 102600 Peoples R China

ISBN: (纸本)9783031054341;9783031054334

To explore the research foundation of experience design through the traceability research of experience design and to clarify the context, boundaries, and connections between different research topics. The integrated advantages of both CiteSpace and vosviewer to draw a knowledge map of related literature on experience design, based on the retrieval results of academic literature related to experience design in the Web of Science academic engine. data and visualization of the research results sort out the highly cited literature on experience design to illustrate bibliometric atlas. The induction method is used to track the four main related fields of experience design, based on quantitative data analysis, combined with our cognition of experience design. From the perspective of the development context and trend of experience design, the experience economy is the commodity experience scenario. The economy determines product form and then design content. The transformation of user experience design to experience design corresponds to changing people's material needs to spiritual needs. Experience management based on process optimization expands the commercialization field of experience design. From the perspective of knowledge cognition and exploration of experience design, macro-leveled experience design coordinates the system and the world, focusing on the long-term construction of macroecology and human cultural environment;meso-experience design tends to be a system centered on customer experience Management;micro-experience design focuses on a complete experience that has a specific meaning or impact on the individual.

关键词： Experience design Bibliometrics visual analysis Development context Research hotspots

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vizInteract: Rapid data exploration Through Multi-touch Interaction with Multi-dimensional visualizations 18th

VizInteract: Rapid Data Exploration Through Multi-touch Inte...

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18th IFIP TC 13 International conference on Human-Computer Interaction (INTERACT)

作者： Chakraborty, Supratim Stuerzlinger, Wolfgang Simon Fraser Univ Sch Interact Arts & Technol Vancouver BC Canada

ISBN: (纸本)9783030856137;9783030856120

Creating and editing multi-dimensional data visualizations with current tools typically involves complex interactions. We present vizInteract, an interactive data visualization tool for touch-enabled displays. vizInteract supports efficient multi-touch data exploration through rapid construction of and interaction with multi-dimensional data visualizations. Building on primitive visualization idioms like histograms, vizInteract addresses the need for easy data exploration by facilitating the construction of multi-dimensional visualizations, such as scatter plots, parallel coordinate plots, radar charts, and scatter plot matrices, through simple multi-touch actions. Touch-based brushing-and-linking as well as attribute-based filter bubbles support "diving into the data" during analysis. We present the results of two explorative studies, one on a tablet and another on a large touchscreen and analyze the usage patterns that emerge while participants conducted visual analytics data exploration tasks in both conditions.

关键词： visualization visual analytics Multi-touch Large touchscreen

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Enhancing Fuel Efficiency in Onshore Drilling Rigs through Generator Power Management: A Sustainable Approach to Reduce Diesel Consumption

Enhancing Fuel Efficiency in Onshore Drilling Rigs through G...

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2024 Offshore Technology conference Asia, OTCA 2024

作者： Chandharabhanich, I. Mekkerdchoo, B. Pensook, T. Amranand, S. Dejdamrongpreecha, W. Jiratawaree, S. Madahin, S. Thongthanawat, C. Amornratanaphan, S. Ruangvanichayakul, v. Kreethapon, T. Panthuvichien, S. Sairuk, C. PTT Exploration and Production Public Company Limited Bangkok Thailand

ISBN: (纸本)9781959025030

This study aims to investigate the impact of generator power management, the use of an auxiliary generator during wireline logging operations, and the implementation of a monitoring system on reducing diesel consumption in drilling rigs. The objectives include optimizing generator power management to achieve the most efficient load range of 70%, utilizing an auxiliary generator during wireline logging to reduce diesel consumption, implementing a monitoring system to ensure effective diesel consumption, and assessing the potential fuel savings and contribution to greenhouse gas reduction efforts and sustainability goals. data was collected from a drilling rig equipped with three main generators and one auxiliary generator. Generator power management techniques were implemented to ensure optimal efficiency by operating the generators within the load range of 70%, minimizing the risk of overload and rig blackouts. During wireline logging operations, the auxiliary generator with lower power output was utilized instead of the main generators, which exceeded the power requirements for wireline logging. A monitoring system was implemented to track and evaluate the effectiveness of diesel consumption in real-time. The results of this study indicate that the implementation of generator power management, the use of an auxiliary generator during wireline logging, and the integration of a monitoring system can lead to significant fuel savings. By optimizing generator power management within the recommended load range, fuel efficiency was improved, reducing diesel consumption. The utilization of the auxiliary generator for wireline logging, which requires lower power output, further contributed to fuel savings. The monitoring system ensured effective diesel consumption by providing real-time data for analysis and adjustment. These initiatives resulted in a reduction of approximately 10% in diesel consumption. The findings of this study demonstrate that the combined implementatio

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Negative Testing: Automating a Safety Critical Process with Human Factors at its Core

Negative Testing: Automating a Safety Critical Process with ...

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2024 SPE Annual Technical conference and Exhibition, ATCE 2024

作者： Bruce, C. Baumgartner, T. Liu, Y. Ali, H. Smith, T. Griffith, S. Kirker, C. Garrett, J. Murphy, D. Tonagel, v. Adeleye, O. Shell Exploration & Production Company United States

ISBN: (纸本)9781959025375

Pressure testing in the oil and gas industry is used to validate the safety and integrity of equipment across a well barrier. Negative testing, also known as inflow testing, requires a negative pressure differential between the well and the formation. This type of pressure testing is used in well systems to test the integrity of a well barrier envelop. The most infamous negative test in oil and gas history was the test on the Macondo well, shortly before the tragic incident unfolded. Current practices vary across the globe, they depend on regional regulations, industry standards, location, and company procedures. The two basic types of approaches are based on analysing volume or pressure data. The most common methods are no-flow, pressure monitoring, and Horner. volume typically is measured using tanks, buckets, and beakers. Pressure traditionally was measured using an analogue pressure chart recorder, which now is increasingly being replaced by real-time data systems. As the oil and gas industry moves towards digital systems for pressure testing, the need for a systematic methodology with clearly defined criteria for negative pressure testing becomes ever more important. Computers cannot interpret ambiguity, so it is essential that a systematic methodology for negative pressure test acceptance is clearly defined, and criteria are developed. This paper proposes a systematic approach aimed at enhancing the interpretation and standardisation of negative pressure testing results with human factors at its core. Drawing from existing literature and an analysis of over 100 negative tests conducted by the operator, seven key principles are established. These principles serve as a unified framework for interpreting negative test results and provide the much-needed detail for automating the acceptance process. Through their application in diverse testing scenarios in deepwater environments, this work identifies potential inconsistencies in the current methodologies and propo

关键词： Gas industry

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visual Event-Based Egocentric Human Action Recognition 10th

Visual Event-Based Egocentric Human Action Recognition

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10th Iberian conference on Pattern Recognition and Image analysis (IbPRIA)

作者： Moreno-Rodriguez, Francisco J. Javier Traver, v Barranco, Francisco Dimiccoli, Mariella Pla, Filiberto Univ Jaume 1 Castellon de La Plana Spain Univ Jaume 1 Inst New Imaging Technol Castellon de La Plana Spain Univ Granada CITIC Dept Comp Architecture & Technol Granada Spain Inst Robot & Informat Ind CSIC UPC Barcelona Spain

ISBN: (纸本)9783031048814;9783031048807

This paper lies at the intersection of three research areas: human action recognition, egocentric vision, and visual event-based sensors. The main goal is the comparison of egocentric action recognition performance under either of two visual sources: conventional images, or event-based visual data. In this work, the events, as triggered by asynchronous event sensors or their simulation, are spatio-temporally aggregated into event frames (a grid-like representation). This allows to use exactly the same neural model for both visual sources, thus easing a fair comparison. Specifically, a hybrid neural architecture combining a convolutional neural network and a recurrent network is used. It is empirically found that this general architecture works for both, conventional gray-level frames, and event frames. This finding is relevant because it reveals that no modification or adaptation is strictly required to deal with event data for egocentric action classification. Interestingly, action recognition is found to perform better with event frames, suggesting that these data provide discriminative information that aids the neural model to learn good features.

关键词： Egocentric view Action recognition Event vision

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Leveraging Deep Learning for Multimodal Predictive Maintenance: A Hybrid CNN-LSTM Approach for Enhanced Equipment Failure Prediction in Automated Assembly Lines

Leveraging Deep Learning for Multimodal Predictive Maintenan...

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IEEE International conference on Power, Intelligent Computing and Systems (ICPICS)

作者： Yelei Rao Southwest Jiaotong University Chengdu China

ISBN: (数字)9798350374315

ISBN: (纸本)9798350374322

The exploration of deep learning techniques for multimodal predictive maintenance in automated production lines is undertaken, presenting a hybrid model that synergizes Convolutional Neural Networks (CNNs) for visual analytics and Long Short-Term Memory (LSTM) networks for temporal sensor data processing. The CNN is designed to pinpoint signs of deterioration and anomalies within visual inputs, while the LSTM extracts predictive patterns from sensor data that indicate equipment failure. Drawing upon a blend of publicly accessible sensor datasets from reputable sources such as the UCI Machine Learning Repository and Kaggle, enriched by an exclusive collection of imagery from a diverse set of 100 Chinese assembly plants, the integrated analysis from both models results in a comprehensive predictive mechanism for equipment malfunction. This pioneering method is intended to enhance the operational efficiency and precision of automated assembly processes through the empowerment of pre-emptive maintenance actions.

关键词： Deep learning Analytical models visual analytics Production Predictive models Maintenance Convolutional neural networks Assembly Long short term memory Predictive maintenance

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