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9th International Conference on Science, Technology, engineering and Mathematics, ICONSTEM 2024

作者： Rajasekar, P. Bhosale, Rupali Shekar Indhumathi, C. Sandeep, K.V. Prasanthi Kumari, N. Rajendiran, M. School of Computing Srm Institute of Science And Technology Department of Data Science And Business Systems Tamil Nadu Kattankulathur603203 India Bharati Vidyapeeth Institute of Technology Department of Electronics And Telecommunication Engineering Maharashtra Navi Mumbai400614 India Rmk College of Engineering And Technology Department of Computer Science And Business Systems Tamil Nadu Puduvoyal601206 India Dayananda Sagar College of Engineering Department of Electronics & Telecommunication Engineering Karnataka Bengaluru560111 India School of Computer Sciences University of Petroleum And Energy Studies Uttarakhand 248007 Dehradun India Panimalar Engineering College Department of Computer Science And Engineering Tamil Nadu Chennai600123 India

ISBN: (纸本)9798350365092

New IoT devices generate massive real-time data. Fast, real-time stream processing is needed for IoT data insight extraction. There are pros and downsides to real-time stream processing for the Internet of Things (IoT). This article analyzes present methods and technologies. The inquiry begins with large-scale, real-time IoT data analysis. Real-time analytics and bulk processing limits are important for IoT decision-making. We then investigate IoT stream processing frameworks, methodologies, and systems' complexity. We explore Internet of Things technology selection and tradeoffs between scalability, accuracy, latency, and real-time processing system scalability. It covers real-time stream processing system design and deployment and risk mitigation. Case studies and use cases highlight real-time IoT stream processing. Healthcare, smart city, and industrial IoT operational efficiency and proactive decision-making improve with real-time data. Finally, the report suggests the Internet of Things real-time stream processing research. New IoT data analytics protocols, methods, and technologies are highlighted. We teach real-time stream processing to IoT academics, practitioners, and decision-makers. They could then develop more efficient and scalable IoT data stream optimization solutions. © 2024 IEEE.

关键词： Edge computing

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Leveraging SDN: Empirical Evaluation of Privacy Enriched Data Communication over VANET Using Software Defined Network Assistance 9

Leveraging SDN: Empirical Evaluation of Privacy Enriched Dat...

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9th International Conference on Science, Technology, engineering and Mathematics, ICONSTEM 2024

作者： Ratheesh, R. Vijayalakshmi, S. Arunsundar, B. Swarna, M. Saranya, G. Agni College of Technology Department of Ece Chennai India R.M.K. Engineering College Department of Ece Chennai India School of Computing College of Engineering And Technology Srm Institute of Science And Technology Department of Data Science And Business Systems Kattankulathur India Dr. M.G.R. Educational And Research Institute University Department of Ece Chennai India Sri Krishna College of Engineering And Technology Department of Electronics And Communication Engineering Coimbatore Kuniyamuthur India

ISBN: (纸本)9798350365092

In the realm of modern transportation systems, Vehicular Ad Hoc Networks (VANETs) play a pivotal role in enabling efficient communication among vehicles and infrastructure elements for enhanced road safety and traffic management. However, the inherent vulnerabilities in VANETs, such as privacy breaches and security threats, necessitate robust frameworks to mitigate risks and ensure secure data transmission. This paper presents a comprehensive architecture for Privacy-Enriched Data Communication over VANETs using Software-Defined Network (SDN) assistance. The proposed framework integrates key components including vehicles, Roadside Units (RSUs), and SDN controllers to facilitate secure and privacy-aware communication. Vehicles act as data sources, employing pseudonyms and encryption mechanisms to protect user privacy. RSUs serve as access points, collecting and relaying data while enforcing access control policies. SDN controllers provide centralized management, dynamically allocating resources and enforcing privacy policies through encryption, pseudonymization, and access control mechanisms. Communication protocols such as IEEE 802.11p and LTE enable vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication, while the OpenFlow protocol facilitates communication between SDN controllers and network devices. Additionally, trust management mechanisms evaluate the trustworthiness of network entities based on behavioral analysis, reliability metrics, and security considerations, ensuring the integrity and resilience of the network. By amalgamating SDN-based management with privacy enhancement mechanisms and trust management protocols, the proposed framework offers a robust solution for addressing privacy and security challenges in VANETs, thereby fostering safer and more secure transportation ecosystems. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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On the Need to Use Smart Contracts in Enterprise Application Integration 25

On the Need to Use Smart Contracts in Enterprise Application...

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25th Ibero-American Conference on Software engineering, CIbSE 2022

作者： Parahyba, Fernando Dornelles, Eldair F. Roos-Frantz, Fabricia Frantz, Rafael Z. Molina-Jiménez, Carlos Reina Quintero, Antonia M. Bocanegra, José Sawicki, Sandro Unijuí University Brazil Department of Computer Science and Technology University of Cambridge United Kingdom Department of Language and Systems University of Seville Spain Department of Systems and Computing Engineering Universidad de los Andes Colombia

ISBN: (纸本)9781713855583

Integration processes involve Business Constraints and Service Level Agreements that, with current technology, are not monitored or enforced automatically at run–time. This approach leaves the participants with no means of supervising the development of their interactions or of collecting indisputable evidence to ease the resolution of disputes that can potentially emerge. In this paper, to address the issue, we suggest the inclusion of smart contracts in integration processes to supervise and mediate, at run–time, the agreements to which the participants commit. We discuss the requirements that smart contracts for integration processes need to meet and the challenges involved in writing, executing, deploying, and verifying them. © 2022 CIbSE 2022 - XXV Ibero-American Conference on Software engineering. All rights reserved.

关键词： Smart contract

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Smart Signaling: A Smart Internet of Things Assisted Traffic Light Controlling and Monitoring System using Intelligent Sensors 9

Smart Signaling: A Smart Internet of Things Assisted Traffic...

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9th International Conference on Science, Technology, engineering and Mathematics, ICONSTEM 2024

作者： Saranya, G. Ratheesh, R. Vijayalakshmi, S. Arunsundar, B. Swarna, M. Sri Krishna College of Engineering And Technology Department of Electronics And Communication Engineering Coimbatore Kuniyamuthur India Agni College of Technology Department of Ece Chennai India R.M.K. Engineering College Department of Ece Chennai India School of Computing College of Engineering And Technology Srm Institute of Science And Technology Department of Data Science And Business Systems Kattankulathur India Dr. M.G.R. Educational And Research Institute University Department of Ece Chennai India

ISBN: (纸本)9798350365092

In contemporary urban environments, efficient traffic management stands as a paramount challenge, necessitating innovative solutions to mitigate congestion, enhance safety, and reduce environmental impact. This paper proposes a Smart Internet of Things (IoT)-assisted Traffic Light Controlling and Monitoring System designed to revolutionize traffic management through real-time data acquisition, analysis, and dynamic control mechanisms. The system integrates edge devices equipped with a variety of sensors, cloud-based infrastructure, and intelligent algorithms to optimize traffic flow at intersections. Leveraging technologies such as AWS IoT, Lambda, and QuickSight, alongside communication protocols like MQTT and HTTP, the system enables seamless device management, secure data transmission, and scalable real-time analytics. Hardware components including microcontrollers, sensors, and actuators facilitate precise data collection, allowing for accurate traffic monitoring and adaptive signal control. Through comprehensive traffic flow analysis, congestion reduction strategies, environmental impact assessments, safety enhancements, and system performance optimizations, the proposed system aims to revolutionize urban traffic management, leading to smoother traffic flow, reduced congestion, improved safety, and enhanced environmental sustainability. © 2024 IEEE.

关键词： Internet of things

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Classification of Helpful and Unhelpful Online Customer Reviews Using XLNet and BERT Variants 1

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International Conference on Green Energy, computing, and Intelligent Technology, GEn-CITy 2023

作者： Bilal, Muhammad Arshad, Muhammad Haseeb Ramzan, Muhammad Department of Computing and Information Systems School of Engineering and Technology Sunway University Petaling Jaya Malaysia Department of Computer Science National University of Computer and Emerging Sciences Chiniot-Faisalabad Campus Chiniot Pakistan Department of Software Engineering University of Sargodha Sargodha Pakistan School of Electronics and Computer Science University of Southampton Malaysia Iskandar Puteri Malaysia

ISBN: (数字)9789819998333

ISBN: (纸本)9789819998326

The majority of businesses have made public appearances on various social media platforms as a result of recent advances in e-commerce and the popularity of social media websites. Customers can share their experiences in the form of online customer reviews, which can assist potential customers in determining the quality of a company and making purchasing decisions. Due to the large volume of published reviews, it becomes difficult for customers to read all of the reviews and assess the quality of the business, resulting in the problem of information overload. Several solutions have been proposed in the literature by researchers using statistical and machine learning techniques to predict the helpfulness of online customer reviews. However, most of the existing solutions are based on the use of various business, review, and reviewer features, which lead to generalizability issues. Moreover, very limited studies have examined the effectiveness of state-of-the-art pre-trained language models for the classification of helpful and unhelpful reviews. Therefore, this study aims to examine the effectiveness of XLNet, Albert, DistilBert, and Roberta for review helpfulness prediction using textual features. The models were fine-tuned using a publicly available dataset of Yelp reviews. The results showed that XLNet achieved the highest F1-score of 0.730 compared to a benchmark of 0.717 achieved by the BERT base model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Sales

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Parameter-efficient fine-tuning of Whisper for low-resource speech recognition

Parameter-efficient fine-tuning of Whisper for low-resource ...

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Artificial Intelligence, Networking and Information Technology (AINIT), International Seminar on

作者： Yunpeng Liu Dan Qu Department of Artificial Intelligence Laboratory for Advanced Computing and Intelligence Engineering School of Information Systems Engineering University of Information Engineering Henan China

ISBN: (数字)9798350385557

ISBN: (纸本)9798350385564

Limited data availability remains a significant challenge for Whisper's low-resource speech recognition performance, falling short of practical application requirements. While previous studies have successfully reduced the recognition error rates of target language speech through fine-tuning, a comprehensive exploration and analysis of Whisper's parameter-efficient fine-tuning capabilities, the advantages and disadvantages are still lacking. This paper aims to fill this gap by conducting comprehensive experimental exploration for Whisper's low-resource speech recognition performance using two parameter-efficient fine-tuning strategies with limited supervised data from multiple low-resource languages. The results and analysis demonstrate that all fine-tuning strategies explored in this paper significantly enhance Whisper's performance. However, different strategies vary in their suitability and practical effectiveness, highlighting the need for careful selection based on specific use cases and resources available.

关键词： Seminars Costs Target recognition Error analysis Speech recognition Data models Task analysis

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AI-Generated Voice in Short Videos: A Digital Consumer Engagement Perspective 44

AI-Generated Voice in Short Videos: A Digital Consumer Engag...

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44th International Conference on Information systems: Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies, ICIS 2023

作者： Luo, Jihao Zheng, Chenxu Yin, Jiamin Teo, Hock-Hai Department of Information Systems and Analytics National University of Singapore 15 Computing Drive 117418 Singapore Department of Management Science and Engineering School of Business Renmin University of China 59 Zhongguancun Road Beijing100872 China

ISBN: (纸本)9781713893622

The AI-generated voice (AIGV) has been widely applied in the short video industry to facilitate video creation. However, the impact of AIGV on digital consumer engagement (DCE) remains unclear. In light of this, the study investigates the effect of AIGV on DCE by analyzing a panel dataset with observations of 21,541 videos for 3,647 content creators on TikTok. Preliminary results of a series of fixed-effect panel regressions reveal that using AIGV has a significantly negative effect on DCE (5.4% reduction in the number of likes, 5.2% reduction in the number of comments, and 7.4% reduction in the number of shares). Our further analyses show that this negative effect is particularly significant at the rising action stage of short videos. With these findings, this study is expected to have theoretical contributions to the literature on short videos and practical implications about the appropriate usage of AIGV. © 2023 International Conference on Information systems, ICIS 2023: "Rising like a Phoenix: Emerging from the Pandemic and Reshaping Hu. All Rights Reserved.

关键词： Information systems

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Deep transfer learning technique to detect white blood cell classification in regular clinical practice using histopathological images

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Multimedia Tools and Applications 2025年第9期84卷 5699-5723页

作者： Davamani, K. Anita Jawahar, Malathy Anbarasi, L. Jani Ravi, Vinayakumar Al Mazroa, Alanoud Robin, C. R. Rene Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India Leather Process Technology Division CSIR-Central Leather Research Institute Chennai India School of Computing Science and Engineering Vellore Institute of Technology Vellore India Computer Science and Engineering Sri Sairam Engineering College Sirukalathur India Center for Artificial Intelligence Prince Mohammad Bin Fahd University Khobar Saudi Arabia Department of Information Systems College of Computer and Information Sciences Princess Nourah bint Abdulrahman University Riyadh11671 Saudi Arabia

Leukemia, a malignant disease characterized by the rapid proliferation of specific types of white blood cells (WBC), has prompted increased interest in leveraging automatic WBC classification system. This study presents the design of a robust WBC classification system, integrating deep learning with microscopic image analysis. The proposed classification model is designed to categorize blood cells into four distinct groups: eosinophil, lymphocyte, monocyte, and neutrophil. The study employs a Kaggle image dataset for comprehensive learning. The dataset comprises 12,500 microscopic images used to categorize the four blood cell groups. To enhance performance and reduce the likelihood of overfitting, transfer learning techniques are employed. Six deep transfer learning models namely VGG16, ResNet50, AlexNet, MobileNet, GoogLeNet, and EfficientNetBO are used for feature extraction and classification. The results of the experiments show that VGG16 and MobileNet demonstrated enhancements compared to other pre-trained models when evaluated on both augmented and original datasets. A diverse set of evaluation criteria was employed to thoroughly assess the effectiveness of medical image classification. Notably, the VGG16 and MobileNet models accurately predicted Lymphocytes and Monocytes with a 100% accuracy rate, and Eosinophil and Neutrophil with rates of 99.35% and 99.81%, respectively. This research work empower medical practitioners, particularly in the field of pathology and hematology by providing advanced tools for accurate blood cell classification. The proposed VGG16 and MobileNet models hold promise for simplifying WBC classification, improving decision-making processes, and ultimately advancing patient care in the medical domain. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Deep learning

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Advances in a DSL to Specify Smart Contracts for Application Integration Processes 25

Advances in a DSL to Specify Smart Contracts for Application...

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25th Ibero-American Conference on Software engineering, CIbSE 2022

作者： Dornelles, Eldair F. Parahyba, Fernando Frantz, Rafael Z. Roos-Frantz, Fabricia Reina Quintero, Antonia M. Molina-Jiménez, Carlos Bocanegra, José Sawicki, Sandro Unijuí University Brazil Department of Language and Systems University of Seville Spain Department of Computer Science and Technology University of Cambridge United Kingdom Department of Systems and Computing Engineering Universidad de los Andes Colombia

ISBN: (纸本)9781713855583

Several languages have been developed for writing smart contracts for specific domains, such as health, finance, and business processes. However, none of them includes the constructors needed for writing smart contracts used in application integration processes which have their own particularities. Such smart contracts are responsible for monitoring the communication between the process and the applications to guarantee that the rights of the parties involved in the integration process are observed. To cover the gap, this paper discusses a domain-specific language for writing smart contracts in the application integration domain. It provides constructors to write smart contracts with a level of abstraction close to the natural language used in conventional contracts. © 2022 CIbSE 2022 - XXV Ibero-American Conference on Software engineering. All rights reserved.

关键词： Smart contract

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Classification of Cacao Pods Ripeness Using Convolutional Neural Networks 16

Classification of Cacao Pods Ripeness Using Convolutional Ne...

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16th International Conference on Ambient systems, Networks and Technologies Networks, ANT 2025 / 8th International Conference on Emerging Data and Industry 4.0, EDI40 2025

作者： Borromeo, Karl O. Bonotan, Melbert R. Llagas, Archie P. Juan, Joana Marie O. Sanchez, Philip Donald C. Berro, Nathan Kit A. Department of Computer Science College of Computing and Information Sciences Caraga State University Butuan City Philippines Department of Information Technology College of Computing and Information Sciences Caraga State University Butuan City Philippines Center for Resource Assessment Analytics and Emerging Technologies College of Engineering and Geo-Sciences Caraga State University Butuan City Philippines Department of Information Systems College of Computing and Information Sciences Caraga State University Butuan City Philippines

This paper presents methods for the development of Ripeness Identification of Cacao Pods using Convolutional Neural Network (CNN) and precision agriculture employed in a Mobile Application. This research explores if there is a correlation between the color dynamics of cacao pods and its physiological characteristics, and the possibility of using this correlation to develop Artificial Intelligence (AI) model for ripeness and variety identification, which conventional eye estimation resulted to unripe and overripe harvesting of Cacao Pods. Data analysis and correlation was developed, integrating detection and classification models based on the Single Shot Detection (SSD) MobileNet and Visual Geometry Group (VGG) 16 or VGG16 layers network architectures, respectively. The mobile application utilizes the TensorFlow template for object detection and incorporates image preprocessing techniques for enhanced accuracy. The successful integration of the model into a mobile application demonstrates its potential for practical applications in the cacao industry. © 2025 Elsevier B.V.. All rights reserved.

关键词： Convolutional neural networks

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