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Sentiment Analysis with Support Vector Machines for Travel Agency Ranking and Traveler Decision Support in Sri Lanka

Sentiment Analysis with Support Vector Machines for Travel A...

引用

Artificial Intelligence (SLAAI-ICAI), SLAAI International Conference on

作者： D. D. M. Jayawardana G. S. N. Meedin H.U.W. Rathnayake Dept. of Electrical and Computer Engineering Faculty of Engineering The Open University of Sri Lanka OUSL Jaela Sri Lanka Dept. of Electrical and Computer Engineering Faculty of Engineering The Open University of Sri Lanka OUSL Colombo Sri Lanka

ISBN: (数字)9798331509170

ISBN: (纸本)9798331509187

Travelers often rely on online reviews to plan trips, but the large volume of data can hinder informed decision-making, especially in the Sri Lankan tourism industry. This research develops a sentiment analysis-based system to help travelers navigate reviews and make informed choices. The system uses Natural Language Processing (NLP) techniques to preprocess and structure user reviews, categorizing them into subcategories like transportation, accommodation, food and beverage, entertainment, recommendations, purpose, and travel agencys. Support Vector Machine (SVM) and Multinomial Naive Bayes (MultinomialNB) classifiers are employed to assess sentiment, classifying reviews as positive, neutral, or negative. The integration of NLP and SVM ensures high accuracy, efficiency, and interpretability in sentiment analysis, enhancing the model’s performance. The designed platform presents travelers with an easy-to-understand bar chart summarizing travel agency reviews and providing actionable insights into service quality. Key metrics like precision, recall, and score validate the model’s effectiveness. By organizing feedback into insights, the system empowers travelers to make better decisions and helps travel agencies identify areas for improvement. The scalable approach allows for adaptation to larger datasets and various tourism contexts, making it a reliable tool for comparing Sri Lankan travel agencies and improving the overall tourism experience.

关键词： Support vector machines Measurement Sentiment analysis Reviews Navigation Tourism industry Transportation Entertainment industry Learning (artificial intelligence) Reliability

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An Improved U-Shaped Network for ROI Segmentation of Skin Lesion Images

An Improved U-Shaped Network for ROI Segmentation of Skin Le...

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Communication & Computing (WCONF), World Conference on

作者： Rasika Gupta Rajeev Kumar Dept. of Computer Science and Engineering Delhi Technological University Delhi India

ISBN: (数字)9798350395327

ISBN: (纸本)9798350395334

Skin cancer, a serious public health concern across the world, is a deadly disease if not diagnosed at an early stage. It is often diagnosed through dermoscopic images that usually have low contrast, irregular boundaries and contains irrelevant artifacts. Due to these factors, the segmentation of Region of Interest (ROI) for effective diagnosis of this disease becomes a challenging task. However, UNet, a U-Shaped Network has proven to be an efficient segmentation model for medical image segmentation, but the result mostly suffers discrepancies with the ground truth segmented mask. Therefore, this paper introduces an improved UNet 3+ architecture with residual block at both encoder and decoder to handle gradient degradation in this deep network, incorporates attention module to focus on relevant features and reduces redundant skip connections. The improved model has been evaluated on publicly available PH2 dataset and achieved an accuracy of 96.62%, dice score of 93.84% and jaccard index of 96.79% on test data. The model surpasses other state-of-the-art UNet models for skin lesion segmentation.

关键词： Image segmentation Accuracy Computational modeling computer architecture Skin Loss measurement Lesions Public healthcare Diseases Skin cancer

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Towards Content Dissemination in Subway Mobility: Re-Evaluating the Performance of Power and Interest Aware PeopleRank

Towards Content Dissemination in Subway Mobility: Re-Evaluat...

引用

IEEE International Conference on Wireless and Mobile Computing, Networking And Communications (WiMob)

作者： Sara Elsingergy Soumaia Al Ayyat Sherif G. Aly Computer Science and Engineering Dept. The American University in Cairo Cairo Egypt

ISBN: (数字)9798350387445

ISBN: (纸本)9798350387452

In this paper, we explore the performance of an opportunistic network forwarding algorithm, namely Power and Interest Aware PeopleRank (PIPeR) in a subway mobility environment. PIPeR is known to perform well according to known metrics in delivering data taking into consideration both the interest in the disseminated data, along with power conservation. The algorithm was only tested however using pedestrian mobility models. Subway mobility is a candidate for many other useful cases for opportunistic content dissemination such as that of armed conflicts where civilian populations live in subway environments for safety without fixed network infrastructure. In this work, we implement and evaluate the PIPeR algorithm in a subway model using the AnyLogic simulator. Our results show a significant increase in the f-measure by 61% and decrease in the delay by 41% in comparison to the pedestrian mobility environment. In addition to that, we pinpoint some areas of interest where content dissemination happens vigorously yet at the expense of some increase in cost and power consumption, which we subsequently alleviate by using a particular hibernation model that decreases the power consumption by 43 % at the expense of only 6% reduction in delivery ratio.

关键词： Measurement Wireless communication Power demand Costs Pedestrians Mobility models Hybrid power systems Delays Safety Public transportation

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Multi-Output Regression for Integrated Prediction of Valence and Arousal in EEG-Based Emotion Recognition

Multi-Output Regression for Integrated Prediction of Valence...

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International Winter Workshop on Brain-computer Interface (BCI)

作者： HyoSeon Choi ChaeEun Woo JiYun Kong Byung Hyung Kim Dept. Electrical and Computer Engineering Inha University Incheon Republic of Korea Dept. Computer Engineering Inha University Incheon Republic of Korea Dept. Artificial Intelligence Inha University Incheon Republic of Korea

Previous research in electroencephalogram (EEG)– based emotion recognition has assumed valence and arousal as independent dimensions and derived results using separate classification models for each. Our study aims to introduce multi- output regression to continuously predict the correlated valence and arousal. We compared the prediction performance of a total of three models: Single-output Regression, Multi-output Regression, and Multi-output Regression with a Chain structure. The analysis yielded the following results: 1) The performance of multi-output and single-output was similar, but the multi-output method is more useful as it can produce multiple outputs at once. 2) Predictions and actuals for valence and arousal were similar. Furthermore, considering that human emotions are not constant during certain intervals, it can provide insights close to the ground truth for understanding changes in emotional states.

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Designing Energy-Efficient PATH-based Decision Tree Memristor Crossbar Circuits

Designing Energy-Efficient PATH-based Decision Tree Memristo...

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IEEE Conference on Nanotechnology

作者： Pranav Sinha Akash Chavan Sunny Raj Dept. of Computer Science and Engineering Oakland University Rochester MI USA

ISBN: (数字)9798350386240

ISBN: (纸本)9798350386257

We propose an approach to designing energy-efficient in-memory decision tree (DT) machine-learning circuits using memristors and PATH-based computing. DT machine learning (ML) algorithms are computationally simple, and they require fewer data to train compared to other ML algorithms, making them an attractive option for edge computing. Existing work on creating energy-efficient DT circuits has utilized FLOW-based computing. However, these approaches require costly write operations before every inference, leading to high energy utilization. In this paper, we propose an algorithm to generate PATH-based DT in-memory crossbar circuit designs that only require a write during circuit synthesis and not before every inference, leading to highly energy-efficient inference. We test the performance of our PATH-based design on multiple standard machine learning datasets and demonstrate that our approach achieves a 47% reduction in energy consumption, on average, compared to the state-of-the-art.

关键词： Machine learning algorithms Memristors Machine learning Energy efficiency Inference algorithms Circuit synthesis Decision trees

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ImportChainBD: Blockchain Solutions for Transparent and Accountable Imported Cosmetic Products

ImportChainBD: Blockchain Solutions for Transparent and Acco...

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Blockchain and Distributed Systems Security (ICBDS), IEEE International Conference on

作者： Md. Adib Khan Sagar Karmoker Ummay Khadiza Rumpa Habibur Rahman Md. Sabbir Hossain Nur Adnan Chowdhury Anik Mahamudul Hasan Dept. of Computer Science and Engineering East West University Dhaka Bangladesh

ISBN: (数字)9798350354348

ISBN: (纸本)9798350354355

To improve the supply-chain management system of Bangladesh for imported cosmetic products this paper proposes a blockchain-based solution. One of the major goals of this project is to increase the tax compliance of the government by stopping counterfeit and illegally imported cosmetic products. Which will enhance the trust of consumers and the brand’s reputation. Using this system is quite easy and convenient, as All the information will be stored in the blockchain, so it will become a secure and immutable product tracking system for importers, distributors, and retailers to maintain their ledgers just by printing and scanning a QR code through an IoT device, and consumers can check the authenticity of these cosmetic products just by scanning them. If the product is verified to be suspicious, The Mobile Court Management System has the power to check its origin. Finally, we can say that it will avoid the sale of counterfeit items in the market and increase government revenue on tax.

关键词： Printing Supply chain management Government Finance QR codes Documentation Blockchains Stakeholders Security Internet of Things

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Enhancing Road Safety Through Fitness-to-Drive Metrics: The NextPerception Project on Driver Behavior Analysis and Gamification

Enhancing Road Safety Through Fitness-to-Drive Metrics: The ...

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Maria Mengozzi Manuel Andruccioli Silvia Mirri Giovanni Delnevo Roberto Girau DISI Dept. of Computer Science and Engineering University of Bolgna Bologna Italy

Driving involves numerous factors demanding a driver's attention. To enhance road safety, there has been a significant increase in the development and implementation of vehicle sensors. These sensors, in conjunction with mobile applications, can assess a driver's emotional state and focus, providing feedback to enhance their attention. This paper explores the monitoring of driver behavior, emphasizing the effects of distractions and emotions on driving performance. Stemming from the European initiative, NextPerception, this research focuses on advancing perception sensors and refining distributed intelligence models in various domains, including automotive. The initiative aims to develop a range of sensors, from obstacle detection tools to those monitoring a driver's eye movements and vital signs. A key goal is to define a “fitness-to-drive” metric, representing the driver's attentiveness level. The project also seeks to use gamification to emphasize the importance of this metric, increasing drivers' awareness of their driving skills. The ultimate aim is to create a system that determines fitness-to-drive based on distractions and emotions, integrating this into a prototype simulating sensor data, and introducing a web-based application to display this data for a community of drivers.

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In-memory Machine Learning using Adaptive Multivariate Decision Trees and Memristors

In-memory Machine Learning using Adaptive Multivariate Decis...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Akash Chavan Pranav Sinha Sunny Raj Dept. of Computer Science and Engineering Oakland University Rochester MI USA

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

We introduce a framework to design in-memory decision tree machine-learning (ML) circuits using memristor crossbars. Decision trees (DTs) offer many advantages over neural networks, such as enhanced energy efficiency, interpretability, safety, privacy, and speed, along with reduced dependence on extensive training data. We propose an adaptive multivariate decision tree (AMDT) training algorithm, which constructs decision trees that incorporate both univariate and multivariate features, facilitating the creation of higher accuracy and energy-efficient crossbar designs compared to the state-of-the-art (SOTA). Our circuits are realized using pure memristor crossbars, requiring just one memristor per cell and no transistors while employing sneak-paths for flow-based in-memory computations. In comparison to the SOTA, our approach produces designs that are, on average, 4% more accurate and require 12.6% lower energy.

关键词： Training Accuracy Circuits Memristors Training data Machine learning Energy efficiency

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TraceChainBD: Securing Supply Chains from Counterfeiting in Bangladesh with Blockchain and IoT Integration

TraceChainBD: Securing Supply Chains from Counterfeiting in ...

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International Conference on Innovations in science, engineering and Technology (ICISET)

作者： Sagar Karmoker Md. Adib Khan Sanjida Alam Lamia Mobinul Ahasan Tanjid Shahriar Sadman Dihan Nur Adnan Chowdhury Anik Dept. of Computer Science and Engineering East West University Dhaka Bangladesh

ISBN: (数字)9798350355499

ISBN: (纸本)9798350355505

The scheme uses blockchain technology in Bangladesh’s supply chain to eliminate counterfeit products, improve tax compliance, and build consumer trust. By ensuring product authenticity, it safeguards brand reputations and boosts government revenue. Manufacturers, distributors, and retailers can enter product data which will then generate QR codes. In case of receiving the product or checking its authenticity, they can scan these QR codes via their mobile or a dedicated IOT device and all the information will be stored in Blockchain. Since blockchain data is secure and immutable, it cannot be altered, consumers can easily check product details by scanning QR codes, and if a product is flagged as suspicious, the Mobile Court Management System can trace its origin. This blockchain-based approach ultimately helps prevent counterfeit goods from entering the market and enhances the government’s ability to collect taxes.

关键词： Technological innovation Supply chain management Manufactured products Supply chains Government Finance QR codes Blockchains Internet of Things Counterfeiting

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Building Network Digital Twins Part I: State Synchronization

Building Network Digital Twins Part I: State Synchronization

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6G Networking (6GNet), International Conference on

作者： John Sengendo Fabrizio Granelli Dept. of Information Engineering and Computer Science University of Trento Trento ITALY

ISBN: (数字)9798350378597

ISBN: (纸本)9798350378603

The Network Digital Twin is emerging as a promising technology for future networks, including 6G, as it allows to gain deep knowledge of its Physical Twin and to perform “what-if“ analyses in a controlled environment. However, while the concept of Digital Twin reached maturity in other fields (such as manufacturing), still the application of this concept to networks presents some relevant challenges. This paper studies the problem of synchronization between the Digital and the Physical Twin, a key functionality to enable the Digital Twin to accurately replicate the behaviour of the Physical Twin. Indeed, accurate synchronization is challenging due to the amount of data to exchange and the delays due to acquisition, modeling and transmission of the related information. The paper analyzes the delay chain in the synchronization process and introduces the concept of “negative delay” through accurate prediction in order to minimize the synchronization delay and enable real-time or “near” real-time synchronization between the Physical and the Digital Twin.

关键词： 6G mobile communication Knowledge engineering Accuracy Buildings Throughput Real-time systems Digital twins Delays Manufacturing Synchronization

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