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FinTech: Deep Learning-Based Sentiment Classification of User Reviews from Various Bangladeshi Mobile Financial Services 1

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proceedings of the 6th IFIP TC 12 international conference on Computational Intelligence in Data Science, ICCIDS 2023

作者： Al Ryan, Abdullah Mahmud, Md. Shihab Mahi, Hasibul Hasan Chowdhury Hossen, Md Shakil Shimul, Nazmul Islam Noori, Sheak Rashed Haider Department of Computer Science and Engineering Daffodil International University Dhaka Bangladesh

ISBN: (数字)9783031382963

ISBN: (纸本)9783031382956

Banking has become an integral part of our lives. Fintech (Financial Technology) skyrocketed the number of people willing to use Mobile Financial Services (MFS) for their daily financial transactions. the banks are providing their services via mobile applications, which can be found on the Google Play Store. these Mobile Financial Services (MFS) provide mobility and increase efficiency by 10-fold. With an astonishing number of users came an abundant number of reviews for these apps. User reviews are the backbone of an application’s success. they provide information about hands-on experience. this study mainly focuses on the reactions of the users of such apps. Sentiment analysis is being used to draw out emotions from the users based on their written reviews. the primary goal of this paper is to examine the points of view of such application users. A total of 5414 pieces of data were collected from the Google Play Store and classified as negative, neutral, or positive. the data model has been evaluated using CNN, LSTM, and BiLSTM algorithms. Compared to CNN and LSTM, the BiLSTM algorithm produced the best model with an accuracy of 97.07%. © 2023, IFIP international Federation for Information Processing.

关键词： Sentiment analysis

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Empowering Real-Time Insights through LLM, LangChain, and SAP HANA Integration 6th

Empowering Real-Time Insights Through LLM, LangChain, and SA...

引用

6th international conference on Recent Innovations in computing, ICRIC 2023

作者： Easin Arafat, Md. Asuah, Georgina Saha, Sourav Orosz, Tamas Data Science and Engineering Department Faculty of Informatics Eötvös Loránd University Pázmány Péter Str. 1/A Budapest1117 Hungary Department of Computer Science and Engineering United International University United City Madani Avenue Dhaka1212 Bangladesh

ISBN: (纸本)9789819734412

Real-time integration within the SAP HANA (High-Performance Analytics Appliance) environment through open-source components signifies a substantial financial investment in information technology (IT) projects. the prevalence of budget overruns, delays in implementation, and imprecise forecasts remain significant factors contributing to project failures. this has led many companies to adopt the usage of real-time insights in planning and decision-making facilities. By keeping the fundamental components of SAP, businesses can upgrade their information systems without having to completely reconfigure them, which proves to be cost-effective. this study initiates an exploration of the intricate integration of large language model (LLM), LangChain, and SAP HANA, underlining the intrinsic value of real-time insights and their multi-faceted applications. the study's main objective is to provide individuals with a road map for utilizing these essential components, customized to their enterprise's specific phase of development. this study highlights how important this integration is and provides a strong push in the direction of operational effectiveness and long-term expansion. the study equally outlines the challenges and considerations of such components in operational effectiveness and long-term expansion. the integrated framework offers the following key benefits, linguistic precision, seamless language-technology integration, and robust analytics infrastructure. As the integrated framework develops, it becomes a revolutionary instrument that changes how real-time insights and decision-making are conducted across a variety of industries. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Budget control

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Urban Arterial Route Travel Time Prediction Using Connected Vehicle Trajectories by Integrating Cloud and Edge Resources 27

Urban Arterial Route Travel Time Prediction Using Connected ...

引用

27th IEEE international conference on Intelligent Transportation systems, ITSC 2024

作者： Chen, Huiyu Wu, Fan Qiu, Tony Z. University of Alberta Department of Civil and Environmental Engineering EdmontonABT6G 1H9 Canada

ISBN: (纸本)9798331505929

In recent years, vehicle trajectory data has become increasingly available from connected vehicles (CVs). CVs, acting as mobile sensors, can cover almost every intersection and provide enriched traffic information. In this context, this study proposed a novel statistical model-based method to predict arterial travel time using CV trajectories. the queue clearing time during green time is assumed to follow a Gamma distribution, and a maximized log-likelihood estimation (MLLE) is utilized to calculate related parameters. A hierarchical framework is further developed to improve both prediction accuracy and efficiency. First, the cloud (i.e., Traffic Management Center [TMC]) estimates the CV penetration rate (PR) and calibrates necessary model parameters offline. then, the network edge (i.e., Mobile Edge computing [MEC]), conducts the prediction online. A route in the City of Edmonton, Canada, is simulated to test the proposed method. the simulated CVs' trajectories are collected to estimate the PR and the cycle-by-cycle queue length at intersections. After that, the MEC at each intersection conducts travel time prediction with the parameters obtained from the TMC. the results achieved a low Root Mean Square Error (RMSE) of travel time prediction, averaging 0.9 minutes. Besides, the running time for a one-hour online prediction only costs 2.3 seconds. © 2024 IEEE.

关键词： Travel time

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5th international conference on Information, Communication and computing Technology, ICICCT 2020

5th International Conference on Information, Communication a...

引用

5th international conference on Information, Communication and computing Technology, ICICCT 2020

ISBN: (纸本)9789811596704

the proceedings contain 24 papers. the special focus in this conference is on Information, Communication and computing Technology. the topics include: GANTOON: Creative Cartoons Using Generative Adversarial Network;time Series Missing Value Prediction: algorithms and Applications;Handling SQL Injection Attack Using Progressive Neural Network;a Novel Automated Method for Detection of Eye Diseases Using Image Processing on Retinal Images;Plant Disease Detection: An Augmented Approach Using CNN and Generative Adversarial Network (GAN);compilation of a Social Network Lexicon for Determining the Profile of Authors;Generalized Constraint Representation of Comparative Adjectives and Its Type-2 Fuzzy Modeling in PNL;homogeneous Pools to Heterogeneous Ensembles for Unsupervised Outlier Detection;FPGA Based Design of Speech Encryption and Decryption for Secure Communication;a Survey of Network Attacks in Wireless Sensor Networks;LiFi Based Scheme for Handover in VANET: A Proposed Approach;Dual-Level Security with Spiral Mapping [DLSSM] Scheme for Secure Covert Transmission of Speech Signals in Various Indian Languages;a Novel Energy Aware Resource Allocation Algorithm into a P2P Based Fog computing Environment;Network Steganography Using Extension Headers in IPv6;partial Migration for Re-architecting a Cloud Native Monolithic Application into Microservices and FaaS;preface;mobility Aware Bandwidth Aggregation Scheme for Heterogeneous Links of Multi-Interface Mobile Node;hand Motion Capturing and Simulation in Medical Rehabilitation Applications;efficient Authentication Protocol for Heterogeneous Wireless Networks;a Novel Transformation Based Security Scheme for Multi-instance Fingerprint Biometric System;smart Parking System to Predict Occupancy Rates Using Machine Learning;analyzing Fuzzy Phrases for Emotion Detection Using Distance Based Approach.

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Artificial Intelligence Application for Security Issues and Challenges in IoT 5

Artificial Intelligence Application for Security Issues and ...

引用

5th international conference on Contemporary computing and Informatics, IC3I 2022

作者： Kwatra, Chetna Vaid Jain, Anupam Royappa, Angelina Bagchi, Susama Babu, S B G Tilak Chowdhary, Harish Lovely Professional University Punjab Pakhwara India Commerce and Management Poddar International College India Velammal Engineering College India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Aditya Engineering College India National Forensic Sciences University School of Doctoral Studies and Research India

ISBN: (纸本)9798350398267

More and more gadgets are getting internet access as a result of advances in technology, collectively known as the 'Internet of things' (IoT). In common parlance, the network of physical and digital components that make up commonplace objects is referred to as the 'Internet of things' (IoT). the Internet of things is a new and exciting area of research thanks to the worldwide proliferation of advanced technologies. One example is the Internet of things (IoT), which lets almost any object, user, service, network, location, or set of circumstances connect with each other. Since IoT's popularity has skyrocketed in the last several years, so have security concerns. AI is at the top of the list because it makes it possible to create complex algorithms, which are needed to protect critical infrastructure like networks, systems, and the Internet of things (IoT). Even so, hackers have learned to use AI to their advantage, and some of them even use AI to do bad things. this article aims to do just that by presenting and summarising the relevant literature in these areas. In order to do this, it gathers information about Internet of things devices, AI systems, AI attacks, and AI defenses. © 2022 IEEE.

关键词： Internet of things

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Reducing Energy Usage and Cost for Environmentally Conscious Cooling Infrastructure 6th

Reducing Energy Usage and Cost for Environmentally Conscious...

引用

6th international conference on Intelligent computing and Optimization, ICO 2023

作者： Hossain, Md. Jakir Akash, Fardin Rahman Ahmed, Sabbir Sarker, Mohammad Rifat Reza, Ahmed Wasif Arefin, Mohammad Shamsul Department of Computer Science and Engineering East West University Dhaka Bangladesh Department of Computer Science and Engineering Daffodil International University Dhaka1341 Bangladesh Department of Computer Science and Engineering Chittagong University of Engineering and Technology Chattogram4349 Bangladesh

ISBN: (纸本)9783031503290

We live in a technological world where everything is powered by electricity. Most of the energy is derived from fossil fuels, a nonrenewable resource. According to the international Energy Agency, only 28% of the world’s energy comes from renewable sources. Residential energy use accounts for around 21% of overall energy consumption in the United States. Our dwellings and other gadgets consume most of our electricity. If we could have passive cooling solutions and more efficient devices, we could reduce our reliance on fossil fuels and our power use. We focused on designing a cost-effective framework for passive cooling and automation. We have covered a passive cooling solution. this study proposes a cost-effective framework combining passive cooling solutions with renewable energy sources to create a greener atmosphere. Our framework utilizes automation to optimize energy consumption and reduce waste. the result is a sustainable living environment that reduces energy consumption and promotes a healthier planet. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Fossil fuels

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Predicting Students’ Final Exam Scores Based on their Regularity of Engagement with Pre-Class Activities in a Flipped Classroom 16

Predicting Students’ Final Exam Scores Based on Their Regul...

引用

16th international conference on Computer Supported Education, CSEDU 2024

作者： Francišković, Teodor Sakal Anđelić, Ana Slivka, Jelena Luburić, Nikola Kovačević, Aleksandar Department of Computing and Control Engineering Faculty of Technical Sciences University of Novi Sad Trg Dositeja Obradovića 6 Novi Sad Serbia

ISBN: (纸本)9789897586972

Flipped Classroom (FC) is an active learning design requiring the students to engage in pre-class learning activities to prepare for face-to-face sessions. Identifying FC learning behaviors that lead to academic success remains a challenge. this paper addresses this challenge by conducting an empirical study in an undergraduate software engineering course employing the FC model. the empirical study draws on the data from an intelligent tutoring system that captured the learning traces of students performing pre-class activities. these traces provided indicators of students’ regularity of engagement, which were then matched to their final exam scores. Regression models were trained to predict final exam scores based on the regularity of engagement indicators. Students were clustered based on their regularity of engagement indicators to uncover actionable feedback for future course iterations. the case study confirms the generalizability of earlier findings that the regularity of engagement is vital for student performance and that course-specific predictors significantly impact the models’ prediction performance. Copyright © 2024 by Paper published under CC license (CC BY-NC-ND 4.0)

关键词： Students

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Sentiment Analysis across Modalities: A Comprehensive Review of Text and Audio Approaches

Sentiment Analysis across Modalities: A Comprehensive Review...

引用

international conference on Recent Trends in Advance computing (ICRTAC)

作者： Krisha Elle Nikita Dhobale Pratiksha Deshmukh Sakshi Nirne Ashwini Jarali Department of Computer Engineering International Institute of Information Technology Pune India

Sentiment analysis, an essential component of natural language processing, reveals the complex web of human emotions and viewpoints present in a variety of communication formats. Text-based as well as audio-based sentiment analysis are two areas where this survey that closely examines sentiment analysis. the digital era’s explosion of textual and auditory data has sparked a great deal of research in these fields, producing a wide range of methods and models. Sentiment analysis algorithms have become increasingly complex as a result of the availability of textual data from sources like social media and news articles. Concurrently, there has been a surge in interest in audio-based sentiment analysis because of the increasing use of audio content in podcasts, customer service interactions, and multimedia platforms. this survey provides an in-depth understanding of the recent methods, techniques and approaches in sentiment analysis using text and audio. It carefully describes in detail various developments in these fields, encouraging interdisciplinary idea-sharing. this paper presents a comprehensive overview of sentiment analysis advancements by offering a comprehensive review of research papers, with a focus on relevant models and techniques.

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Creative Research on Automatic Detection of Flying Objects

Creative Research on Automatic Detection of Flying Objects

引用

6th international conference on Intelligent computing and Signal Processing (ICSP)

作者： Lu Liu Yiyang Lu Binrui Xu Heyang Peng Yuhan Ren College of International Education SiChuan Normal University Chengdu China Faculty of Computing Harbin Institute of Technology Harbin China School of Information Science and Engineering Harbin Institute of Technology Harbin China Law School SiChuan Normal University Chengdu China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

With the increasing development of China's modernisation and the growing demand for national defence security, it is very important to detect unidentified flying objects in the air and eliminate potential threats to ensure national security. In order to solve the dual problems of high cost of manual inspection and poor performance of the detection model with low accuracy, this paper proposes a way to automate the detection of flying objects by using the YOLOv5 target detection model, improving the loss function CIOU_Loss to EIOU_Loss by default to speed up the convergence speed of the model, and at the same time adopting a variety of novel data enhancement methods to improve the accuracy. this paper also compares the performance of the YOLOv5 model before and after the improvement in the training and flying objects detection process to demonstrate the effectiveness of the improvement.

关键词： YOLO Training Accuracy Atmospheric modeling Computational modeling Signal processing algorithms Signal processing Data models Security Convergence

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Optimization analysis of 5G+ frequency allocation problem and simulation experiments of some existing optimization algorithms 4

Optimization analysis of 5G+ frequency allocation problem an...

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4th IEEE international conference on Civil Aviation Safety and Information Technology, ICCASIT 2022

作者： Zhang, Yitao Major in Telecommunications Engineering with Management International School Beijing University of Posts and Telecommunications Beijing100000 China

ISBN: (数字)9781665467667

ISBN: (纸本)9781665467667

Since its birth, mobile communication has developed rapidly and has become the basic information network connecting human society. Now, the future oriented fifth generation mobile communication has become a global research and development hotspot. the fifth generation mobile communication technology is the latest generation of cellular mobile communication technology, which is also an extension after 4G (LTE-A, WiMAX), 3G (UMTS, LTE) and 2G (GSM) systems. Its performance goal is high data rate, reduce latency, save energy, reduce cost, improve system capacity and large-scale equipment connection. With the further development of intelligent communication, cloud computing, big data and other technologies are also emerging day by day. these technologies not only make the transmission of data information more convenient, but also meet the requirements of information data conversion and storage, and provide greater convenience for the expansion of communication network services.[1] the main content of this paper is optimization analysis of 5G+ frequency allocation problem and simulation experiments of some existing optimization algorithms. Integer frequency reuse (IFR) is a network structure that can optimize frequency allocation, and the intelligent optimization algorithms of simultaneous water filling (SWF) and transmit interference temperature limit (tx-ITL) based on integer frequency reuse (IFR) can greatly improve the user capacity and optimize frequency allocation. © 2022 IEEE.

关键词： Frequency allocation

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