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Stock Market Growth and Decline Using ARIMA Model and Sentiment Analysis

Stock Market Growth and Decline Using ARIMA Model and Sentim...

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International Symposium on Advanced computing and Communication (ISACC)

作者： Sandipan Biswas Bhaskar Roy Sujit Kumar Singh Nitin Nitin Saroj Kumar Sahoo Sanjaya Kumar Sarangi Dept. of CSE-AI Brainware University Kolkata India Dept. of CSE(AIML) Asansol Engineering College Asansol India Faculty of Information Technology and Computer Science Parul University Vadodara India Department of CSE Akhilesh Das Gupta Institute of Professional Studies Delhi India Department of CSE Centurion University of Technology and Management Bhubaneswar India Dept. of Computer Science Utkal University Bhubaneswar India

ISBN: (数字)9798331523893

ISBN: (纸本)9798331523909

Researchers have been developing and entering the technological era since the 18th century. Before everyone else, social networks brought people from distant nations together. Social network applications such as Reddit, Twitter, Facebook, Instagram, LinkedIn, and others are examples of associate degree programs. Each application has a unique purpose. Investors who want to buy stocks take use of this social networking information. They stay up with a few companies thanks to this information. In order to assess people's sentiments regarding a certain stock, we will be using stock-related news data in this instance. Using TEXTBLOB sentiment analysis, this analysis will provide feedback on the corporate so that we may be prepared to see a rise or fall in relation to investors or firm performance.

关键词： Sentiment analysis Analytical models Social networking (online) Time series analysis Predictive models Data models Web sites multimedia communication Stock markets Intelligent systems

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Improving essential knowledge and self-efficacy in computers network course: The potential of chatbots 27

Improving essential knowledge and self-efficacy in computers...

引用

27th International conference on Knowledge Based and Intelligent Information and Engineering Sytems, KES 2023

作者： Ahmed, Mahmoud Mohamed Hussien Hasnine, Mohammad Nehal Instructional Technology Department South Valley University Qena83523 Egypt Research Center for Computing and Multimedia Studies Hosei University Tokyo184-8584 Japan

In university-level education, the computer network is a mandatory course for computer science and engineering majors. A computer network course provides theoretical and hands-on foundations for network connectivity, network topologies, internet protocols, networking devices, and gateways. In the traditional classroom, students face challenges in gaining essential knowledge and self-efficacy. Teachers face challenges in assessing students' quality of knowledge due to the abundance of online computer science teaching resources. Chatbot technologies have the potential to overcome these challenges and enhance essential knowledge and self-efficacy. However, the argument remains whether a course-specific standard chatbot or a generalizable chatbot could produce high-quality answers. Therefore, in this paper, we research 1) to what extent does using chatbots improve higher education students' essential knowledge of computers network? and 2) to what extent does using chatbots improve the self-efficacy of higher education students? Our first insight indicates that groundbreaking generalizable chatbots such as You and ChatGPT produce rather detailed answers to the questions associated with computer network courses, but those answers may not be the model answers that teachers expect from the students. Hence, research-based course-specific standard chatbots are required to teach computer network topics effectively. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)

关键词： Chatbots computer network education essestial knowledge higher education self-efficacy

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Reinforcement Learning Based QoS-Aware Anti-Jamming Underwater Video Transmission

Reinforcement Learning Based QoS-Aware Anti-Jamming Underwat...

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IEEE conference on Wireless Communications and networking

作者： Shiyu Sun Shun Chen Shaoxuan Li Zefang Lv Liang Xiao Wei Su Dept. of Information and Communication Engineering Xiamen University Xiamen China Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China Xiamen University China

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

Underwater video transmission has to ensure quality-of-service (QoS) against jamming with severe multipath effect and narrow bandwidth limitation that degrade the communication performance under variable channel state. In this paper, we propose a reinforcement learning (RL)-based QoS-aware underwater video transmission scheme to optimize the video compression ratio, modulation format and transmit power based on the state consisting of the channel gain and previous transmission performance. This scheme evaluates the risk level that indicates the probability of failing the QoS and the long-term expected utility of each transmission policy under the current state to improve the anti-jamming communication performance. We derive the performance bound of the utility and analyze its relationship with transmission policy. Simulation results illustrate that our scheme improves the QoS by reducing the frame loss rate (FLR), transmission delay and increasing spatial-spectral entropy-based quality (SSEQ) compared with the benchmark.

关键词： Transmitters Simulation Modulation Quality of service Reinforcement learning Benchmark testing Video compression

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Multi-modal Learnable Queries for Image Aesthetics Assessment

Multi-modal Learnable Queries for Image Aesthetics Assessmen...

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IEEE International conference on multimedia and Expo (ICME)

作者： Zhiwei Xiong Yunfan Zhang Zhiqi Shen Peiran Ren Han Yu College of Computing and Data Science Nanyang Technological University Singapore Alibaba-NTU Singapore Joint Research Institute Nanyang Technological University Singapore Alibaba Group Hangzhou China

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

Image aesthetics assessment (IAA) is attracting wide interest with the prevalence of social media. The problem is challenging due to its subjective and ambiguous nature. Instead of directly extracting aesthetic features solely from the image, user comments associated with an image could potentially provide complementary knowledge that is useful for IAA. With existing large-scale pre-trained models demonstrating strong capabilities in extracting high-quality transferable visual and textual features, learnable queries are shown to be effective in extracting useful features from the pre-trained visual features. Therefore, in this paper, we propose MMLQ, which utilizes multi-modal learnable queries to extract aesthetics-related features from multi-modal pre-trained features. Extensive experimental results demonstrate that MMLQ achieves new state-of-the-art performance on multimodal IAA, beating previous methods by 7.7% and 8.3% in terms of SRCC and PLCC, respectively.

关键词： Visualization Social networking (online) Feature extraction

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Evaluating Channel and Appeal Effectiveness to Optimize Digital Campaigns in Fashion Marketing

Evaluating Channel and Appeal Effectiveness to Optimize Digi...

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Advancements in Electrical, Electronics, Communication, computing and Automation (ICAECA), International conference on

作者： Latha A Sangeetha S Elankumaran R Department of Management Studies Kumaraguru College of Technolgyy Coimbatore India

ISBN: (数字)9798331525439

ISBN: (纸本)9798331525446

In the dynamic digital marketplace, Valayaa, a Coimbatore-based startup specializing in handcrafted silk bangles, relies heavily on social media platforms to promote its unique fashion accessories. Despite targeting upper-middle-class and premium-segment women who value artisanal craftsmanship, tradition, and contemporary design, the brand has faced challenges in achieving a high return on investment (ROI) and effectively reaching potential customers. This study evaluates the performance of two advertising campaigns drafted with two different emotional appeals titled Mother’s Treasure (appeal focusing Innocent & Playful) and Bangles Woven with Love (focusing sentiment and joyfulness) executed across Facebook, Instagram, and YouTube to identify key insights for optimizing digital marketing *** reveal that Bangles Woven with Love, an appeal-driven campaign centered on elegance and heritage, secured the highest click-through rate (CTR) and reach, while Mother’s Treasure, an emotionally resonant campaign celebrating maternal bonds, achieved the highest return on ad spend (ROAS) on Instagram. This highlights the significance of emotional and aspirational appeals in driving engagement and conversions. The study suggests M/s Valaya enhance campaign performance through refining audience targeting, leveraging high-performing platforms, and consistently tracking key performance indicators (KPIs) to enhance campaign effectiveness

关键词： Video on demand Target tracking Social networking (online) Refining Key performance indicator Focusing Weaving Telecommunication computing Web sites multimedia communication

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Colored Ant for Flow Management in Fog computing 4

Colored Ant for Flow Management in Fog Computing

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4th International conference on Communications, Signal Processing, and their Applications, ICCSPA 2020

作者： Sethom, Kaouthar INNOV’COM Lab SUPCOM University of Carthage Tunisia

ISBN: (纸本)9781728165356

Nowadays, users’ demands are increasing in terms of data volume, interactivity, and multimedia quality. This put higher challenges on providers. Cloud operators are trying to improve network performance to fulfill application requirements and satisfy customers. However, this objective is still increasing in difficulty. Software-Defined Network (SDN) offers a new vision of the networking paradigm with more management flexibility. It simplifies networking by providing global visibility through a central controller. In this paper, we propose a new QoS aware flow management based on the SDN technique and Ant optimization algorithm in the scenario of Fog computing. The per-flow decision is taken more efficiently in the centralized controller based on specific metrics and flows classification. Performance experiments based on our implementation shows promising results. © 2020 IEEE

关键词： Ant colony optimization

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Evaluating multimedia Protocols on 5G Edge for Mobile Augmented Reality 17

Evaluating Multimedia Protocols on 5G Edge for Mobile Augmen...

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17th IEEE International conference on Mobility, Sensing and networking (MSN)

作者： Cao, Jacky Su, Xiang Finley, Benjamin Pauanne, Antti Ammar, Mostafa Hui, Pan Univ Oulu Oulu Finland Norwegian Univ Sci & Technol Gjovik Norway Univ Helsinki Helsinki Finland Georgia Inst Technol Atlanta GA 30332 USA Hong Kong Univ Sci & Technol Hong Kong Peoples R China

ISBN: (纸本)9781665406680

Mobile Augmented Reality (MAR) mixes physical environments with user-interactive virtual annotations. Immersive MAR experiences are supported by computation-intensive tasks, which are typically offloaded to cloud or edge servers. Such offloading introduces additional network traffic and influences the motion-to-photon latency (a determinant of user-perceived quality of experience). Therefore, proper multimedia protocols are crucial to minimise transmission latency and ensure sufficient throughput to support MAR performance. Relatedly, 5G is a potential MAR supporting technology and is widely believed to be faster and more efficient than its predecessors. However, the suitability and performance of existing multimedia protocols for MAR in the 5G edge context have not been explored. In this work, we present a detailed evaluation of several popular multimedia protocols (HLS, MPEG-DASH, RTP, RTMP, RTMFP, and RTSP) and transport protocols (QUIC, UDP, and TCP) with a MAR system on a real-world 5G edge testbed. The evaluation results indicate that RTMP has the lowest median client-to-server packet latency on 5G and LTE for all image resolutions. In terms of individual image resolutions, from 144p to 480p over 5G and LTE, RTMP has the lowest median packet latency of 14.03 +/- 1.05 ms. Whereas for jitter, HLS has the smallest median jitter across all image resolutions over LTE and 5G with medians of 2.62 ms and 1.41 ms, respectively. Our experimental results indicate that RTMP and HLS are the most suitable protocols for MAR.

关键词： multimedia protocols mobile augmented reality 5G edge computing

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Image Denoising using Multiscale Transforms

Image Denoising using Multiscale Transforms

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International conference on computing and networking Technology (ICCNT)

作者： Itreddy Shyam Sundar Reddy Kakarla Bhanu Prakash Panyam Hemanth Reddy Tripty Singh Adirath Mandal Suman Chatterjee Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India Graphic Era Dehradun Uttarakhand India Dept of Mechanical Engineering Kongju National University Cheonan South Korea

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

A crucial step in multimedia processing is image and video denoising, which aims to eliminate undesirable noise while keeping significant image properties. This research investigates the use of four distinct multiscale transforms for picture denoising: ridgelets, shearlets, curvelets, and wavelets. To capturing and displaying visual structures at different scales and orientations, each transform offers special features. Through studies on artificial and real-world noisy images, examine each method’s denoising performance and compare its capacity to reduce noise while maintaining image information. The outcomes demonstrate the advantages and disadvantages of each strategy and shed light on how well they work with various kinds of noise and image content. This study investigates the effects of four different multiscale transforms (ridgelets, shearlets, curvelets, and wavelets) on the Signal-to-Noise Ratio (SNR) in addition to examining their denoising capabilities. SNR values are important measurements for assessing how well denoising works since they offer measurable information on how to strike a balance between noise reduction and detail preservation in the image. Through extensive experiments on synthetic and real-world noisy photos, this study evaluates the effectiveness of every denoising technique over a range of noise kinds and image contents. The abstract also emphasizes the distinct qualities that every multiscale transform offers in terms of capturing and expressing visual structures at different scales and orientations. By means of a thorough examination, the research reveals the benefits and drawbacks of every technique, providing significant understanding regarding their appropriateness for various denoising situations.

关键词： Wavelet transforms Visualization Noise reduction Streaming media Noise measurement Signal to noise ratio Image denoising

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EDGE ENHANCEMENT NETWORK FOR WEAKLY SUPERVISED SEMANTIC SEGMENTATION

EDGE ENHANCEMENT NETWORK FOR WEAKLY SUPERVISED SEMANTIC SEGM...

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2021 IEEE International conference on multimedia and Expo, ICME 2021

作者： Yu, Mei Wei, Junbin Wang, Chenhan Jiang, Han Yu, Jian Zhang, Ruixuan Li, Xuewei Yu, Ruiguo College of Intelligence and Computing Tianjin University China Tianjin Key Laboratory of Cognitive Computing and Application China Tianjin Key Laboratory of Advanced Networking China Tianjin International Engineering Institute Tianjin University China OpenBayes Inc Beijing China

ISBN: (纸本)9781665438643

It is difficult and expensive to obtain labels for image semantic segmentation tasks. This has led to more and more researches focusing on weakly supervised semantic segmentation (WSSS) with image-level labels and the class activation maps (CAM) is often used to locate objects. The performance of WSSS methods largely depends on the accuracy of the generated CAMs, but current methods can only perform rough localization, especially cannot fit CAM to the object's edge well. Therefore, we propose the Edge Enhancement Network (EEN), which uses the shallow features of the network to enhance edge information. This allows us to obtain more accurate CAMs that fit the edges only through image-level labels. It greatly improves the accuracy of pseudo ground truth and easily reaches the level of current mainstream methods. After many experiments, it has reached 67.0% mIoU on the Pascal VOC2012 validation set, which exceeds the latest method under the same training settings. © 2021 IEEE

关键词： Semantic Segmentation

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Understanding Brand's Association: Fine-Grained Multi-Modal Content Discovery for Brands

Understanding Brand's Association: Fine-Grained Multi-Modal ...

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International conference on Behavior, Economic and Social computing (BESC)

作者： Shuhan Qi Chengkai Huang Yifan Li School of Computer Science and Technology Harbin Institute of Technology Shenzhen Shenzhen China School of Computer Science and Engineering The University of New South Wales Sydney Australia

ISBN: (数字)9798331531904

ISBN: (纸本)9798331531911

With the increasing popularity of short video plat-forms, the massive UGC provides high-quality materials for brand advertising. Recently, personalized content discovery methods have been proposed to recommend appropriate posts for brands to attract potential consumers. However, there are some drawbacks of them. Firstly, these methods only use images but ignore the multimodal information, which is not suitable for video-based brand advertising. Secondly, the generated features of brands are too coarse to distinguish the subtle differences from similar brands. In this paper, we propose a fine-grained multimodal content discovery (FGMCD) framework, which uses a large number of multimodal data to recommend informative videos for brands. Further, we designed a new hierarchical model, which adopts fine-grained features of different levels to make distinctions of similar brands exactly. We also collect a high-quality dataset with 50 car brands from Instagram and the experiments show the effectiveness of our method.

关键词： Visualization Social computing Social networking (online) Computational modeling Feature extraction Automobiles Web sites multimedia communication Advertising

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