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3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Tanvi, Y. Lakshmi Sowmya, B. Prashanth, B.N. Rajagopal, Shinu M. Dept. of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India Dept. of Electronics and Communication Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru India Dept. of Mechanical Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

The rapid increase in urban vehicle numbers has significantly worsened traffic congestion, particularly in public parking spaces, where conventional parking systems often prove inefficient, leading to wasted time, excessive fuel consumption, and increased environmental pollution. A Smart Car Parking System is proposed to address these challenges by integrating advanced technologies, including the Internet of Things (IoT), to optimize parking operations. The system employs sensors embedded in parking spaces to detect vehicle presence and provide real-time data on availability. This enables drivers to locate free parking spaces efficiently, improving traffic flow. Additionally, the system offers valuable insights to city planners and facility managers, supporting optimal space allocation and dynamic pricing models. By reducing vehicle idling and unnecessary driving while searching for parking, the system helps minimize emissions, contributing to environmental sustainability. The study builds an automated smart car parking system for parking slot monitoring and gate control. The system ensures correct slot occupancy reading, status displayed in real time, and smooth operation of an opening and closing system. It manages additional features such as real-time sensor calibration and effective gate control with a high degree of accuracy and accountability. The proposed Smart Car Parking System represents a key innovation in urban mobility, offering a user-friendly, efficient, and ecofriendly solution to one of the most persistent challenges faced by modern cities. © 2025 IEEE.

关键词： Traffic congestion

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Exploring the Impact of Conditional Deep Convolutional Generative Adversarial Networks in Brain Tumor Image Classification: A Novel Approach

Exploring the Impact of Conditional Deep Convolutional Gener...

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2025 International Conference on Pervasive Computational Technologies, ICPCT 2025

作者： Upadhyay, Deepak Upadhyay, Abhay Sharma, Kuj Bihari Dhondiyal, Shiv Ashish Venu, Nookala Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era Deemed to Be University Dept. of Computer Science and Engineering Dehradun India Centre for Internet of Things Madhav Institute of Technology & Science Deemed University Gwalior India

ISBN: (纸本)9798331508685

In this paper, we explore the impact of conditional Deep Convolutional Generative Adversarial Networks (cDCGANs) with brain tumor image classification and introduce a new way to improve diagnosis accuracy. Shortage of Data/Data Imbalance: In Medical Imaging datasets, it helps in surging the data scarcity and class imbalance with mimicking generation images using cDCGAN. The detailed investigation demonstrates that synthetic data effectively improves classifier performance by acting as a form of augmentation, providing additional training examples for classifiers and serving as ground truth. From the computational efficiency analysis, we see that there is also scalability in training time with respect to dataset size. Consequently, this study presents cDCGANs as an important asset with which to improve diagnostic accuracy through brain tumor categorization in clinical contexts. © 2025 IEEE.

关键词： Generative adversarial networks

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Cost-balanced Adaptive Replica Server Cache Management under Time-Varying User Request Density in CCDNs 14

Cost-balanced Adaptive Replica Server Cache Management under...

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14th IEEE International Conference on Communication Systems and Network Technologies, CSNT 2025

作者： Gupta, Rohit Kumar Mazumdar, Arka Prokash Dept. of Computer Science & Engineering Malaviya National Institute of Technology Jaipur Manipal University Jaipur India Dept. of Computer Science & Engineering Malaviya National Institute of Technology Jaipur Jaipur India

ISBN: (纸本)9798331531935

In today’s growing Internet, cost-effective on-demand provisioning of caching resources in Cloud-based Content Delivery Networks (CCDNs) is essential to preserve the cache hit ratio while reducing storage requirements. However, during the high and fluctuating request rates at different locations, the sudden increase in cache to mitigate the miss rate requires a balance between storage cost (from dynamic cache provisioning) and miss cost (from latency in retrieving content from the Origin Server (OS) or other Replica Servers (RSs)). In such an environment, some RS instances remain underutilized while others are overburdened across different locations and time intervals, which requires effective RS management to activate only sufficient RSs by adapting to the user demands. To overcome these challenges, a cost-balanced adaptive cache management approach is proposed for dynamic cache provisioning in CCDN. This method aims to dynamically manage the activation of RS to optimize resource utilization, and cache instance provisioning and content caching operations in these RSs are managed by introducing an Adaptive Cache Manager that retrieves content from the OS or other RSs by effectively balancing costs in different time intervals. The experimental results indicate that the proposed method reduces the number of active replica servers in CCDN across different time intervals while decreasing the average total cost by about 56% relative to the LRU caching policy on fixed cache and about 10% compared to the dynamic selective caching policy on RCW cache. © 2025 IEEE.

关键词： Cache memory

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A Study on the Evaluation of Cyber Security Vulnerabilities in Medical Software

A Study on the Evaluation of Cyber Security Vulnerabilities ...

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2025 International Conference on Electronics, Information, and Communication, ICEIC 2025

作者： Woo, Jeong-Hyun Koo, Jee-Hyun Seo, Byung-Suk Son, Sun-Young Ko, Kwang-Man Sang-Ji University Dept. of Computer Engineering Korea Republic of Sang-Ji University Dept. of Bigdata Science Korea Republic of Sang-Ji University Dept. of Electrical and Electronic Engineering Korea Republic of

ISBN: (纸本)9798331510756

In this paper, we examine the cybersecurity vulnerability assessment method of medical software. Medical software processes patient sensitive data and is linked to various medical devices and systems in real time. Due to these characteristics, medical software is highly likely to be exposed to various cybersecurity threats such as ransomware, data leakage, and medical device hacking. Based on the international standard IEC TS 60601-4-5, we propose threat modeling, vulnerability scanning, and penetration testing as a methodology for assessing the security vulnerabilities of medical software. Through this, we can identify security vulnerabilities in advance and prepare measures to respond quickly. We can prevent security threats and improve the safety of medical software through response strategies such as security patches and updates, network separation, data encryption, and security education. In conclusion, strengthening the security of medical software is essential to maintain patient safety and the reliability of the medical system, and systematic security assessment and continuous response are required. © 2025 IEEE.

关键词： Cyber attacks

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COMPACT: Content-aware Multipath Live Video Streaming for Online Classes using Video Tiles 25

COMPACT: Content-aware Multipath Live Video Streaming for On...

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16th ACM Multimedia Systems Conference, MMSys 2025

作者： Chaudhary, Shubham Mishra, Navneet Gambhir, Keshav Rajore, Tanmay Bhattacharya, Arani Maity, Mukulika Dept. of Computer Science & Engineering IIIT Delhi Delhi New Delhi India

ISBN: (纸本)9798400714672

The growing popularity of live online classes, even in remote areas, stresses the need for a good and seamless quality of experience to enhance learning. However, these bandwidth-hungry applications challenge the current cellular networks to maintain consistent bandwidth and latency. In this work, we, therefore, propose using the collaboration of multiple devices with their individual cellular networks to support such live video streaming. We design a content-aware system Compact that splits video into foreground and background using video tiles (independently encoded spatial blocks) and streams them over different paths. Compact depends on its scheduler, which exhaustively searches for the best quality based on the network estimates. We extensively evaluate our system using network traces while walking and traveling on the bus or car. Compared to the single path, Compact manages to reduce the median stall and E2E lag by 70.6% and 28.57%, and the tail stall and lag by 83.9% and ≈ 80% on a bus trace. Furthermore, we performed a live experiment to test Compact on the actual cellular network. © 2025 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Mobile telecommunication systems

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Effect of Alternate Cementation Reagent and Soil Moisture on Leachability of Heavy Metals in Soil Remediated Using Bacillus subtilis

Effect of Alternate Cementation Reagent and Soil Moisture on...

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Geo-EnvironMeet 2025: Geoenvironmental Contamination and Waste Containment

作者： Kulkarni, Kalyani Jain, Nehal Babu, G. L. Sivakumar Centre for Sustainable Technologies Indian Institute of Science Bangalore India Dept. of Civil and Environmental Engineering Univ. of Illinois at Urbana-Champaign IL United States Civil Engineering Dept. Centre for Sustainable Technologies Indian Institute of Science Bangalore India

ISBN: (数字)9780784485699

Using bacteria to improve soil characteristics is a sustainable solution that is gaining popularity. The bacteria are often used in combination with cementation reagents (CR) comprising of calcium chloride (CaCl2) and urea. However, CaCl2, which is also used in soil washing of heavy metal-contaminated soils, showed an increase in the leachability of heavy metals. Hence, calcium hydroxide [Ca(OH)2] was experimented as an alternative source of Ca along with Bacillus subtilis and incubation at different moisture contents. Tests were conducted on the leachability of Cadmium (Cd), Nickel (Ni), and Zinc (Zn)-contaminated red soil and dredged sediment. While both were spiked with the same concentration of heavy metals and subjected to the same bacterial concentration, minimum leachability was observed after 4 days for 1M concentration when incubated at 100% moisture in the soil. Ca(OH)2 was observed to reduce the leachability to the maximum extent for all these heavy metals. © ASCE.

关键词： Soil moisture

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The influence of composite modification of precursor and activator on the properties of the silica-aluminum phosphate geopolymer

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Ceramics International 2025年第10期51卷 13317-13329页

作者： Zhao, Fu Xie, Xiaoli Huang, Rong Zhang, Jiufu Taieh, Nabil Kadhim Gou, Guangjun Lin, Xiao Xie, Hecheng School of Materials and Chemistry Southwest University of Science and Technology Mianyang621010 China School of Civil Engineering Lanzhou University of Technology Lanzhou730050 China Materials Techniques Engineering Dept. Middle Technical University Baghdad10001 Iraq

The silica-aluminum phosphate (SAP) geopolymers were fabricated from the precursors containing metakaolin (MK) and CaO, as well as the activators containing phosphoric acid (PA) and aluminum dihydrogen phosphate (ADP). The working performance and mechanical properties of the geopolymers, with CaO replacing MK contents ranging from 6 to 9 wt% and ADP replacing PA contents ranging from 10 to 40 wt%, were investigated. Moreover, the geopolymers without CaO and ADP were fabricated as the control samples. As a result, the SAP geopolymers modified by ADP and CaO showed significant improvement in the working and mechanical properties. Compared with the control sample, the measurements of the fluidity, setting times and compressive strength of the optimal sample with 8 wt% CaO and 20 wt% ADP was found to be increased by 81 %, shortened by 64 % and increased by 66 %, respectively. The results of the heat release analysis showed that adding either CaO or ADP decreased the total heat release of the geopolymers;adding CaO increased the heat release rate at the first 30 min of the geopolymers, whereas ADP decreased the heat release rate of the geopolymers. The XRD and SEM-EDS analysis indicated that incorporating CaO and ADP promoted the formation of the geopolymer network, which contributed to the improvement of the mechanical properties of the geopolymers. In addition, the pore structure analysis revealed that adding CaO could significantly increase the percentage of harmless pores in the structure of the geopolymers, improving the mechanical properties of the geopolymers. © 2025 Elsevier Ltd and Techna Group S.r.l.

关键词： Compressive strength

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A glimpse ahead: Forecasting 5.5-s human vigilance for enhanced safety in Industry 5.0

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Biocybernetics and Biomedical engineering 2025年第2期45卷 258-268页

作者： Cinquetti, Ettore Siviero, Ilaria Babiloni, Fabio Menegaz, Gloria Storti, Silvia F. Dept. of Computer Science University of Verona Verona Italy Dept. of Engineering for Innovation Medicine University of Verona Verona Italy Dept. of Molecular Medicine Sapienza University of Rome Rome Italy

In the context of Industry 5.0 and human-robot interaction, ensuring the safety of operators by avoiding human errors is crucial. Monitoring vigilance decrement is an essential aspect of this effort, aimed at mitigating safety risks and enhancing productivity. A potentially promising solution to this challenge is using a passive brain-computer interface (BCI) based on electroencephalography (EEG) recordings. However, its application in industrial settings has yet to be explored in-dept.. This study uses EEG data to introduce a novel experimental protocol and analysis pipeline to predict vigilance degradation in an industrial research laboratory. The dataset was gathered from ten healthy volunteers who observed a robotic arm for 23 min. The EEG power spectrum over time was computed using the continuous wavelet transform (CWT). After confirming growth in power for the α band using a linear regression model, we forecast its trend using four models. As a conventional approach, we used the vector autoregressive (VAR) model, serving as a reference for comparison with three deep learning architectures: a temporal convolutional network (TCN), a gated recurrent unit (GRU) and an encoder-decoder (ED)-GRU. The proposed ED-GRU model outperformed the others showing accurate forecasts (mean absolute error = 0.048, R² = 0.726) up to 5.5 s. The findings suggest that monitoring vigilance degradation in Industry 5.0 is a feasible strategy to prevent human accidents and reduced performance during repetitive tasks. © 2025 Nalecz Institute of Biocybernetics and Biomedical engineering of the Polish Academy of sciences

关键词： Brain-computer interface Deep-learning Electroencephalography Forecasting Industry 5.0. Vigilance

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Predicting Customer Purchase Intent Using Logistic Regression: A Data-Driven Approach 2

Predicting Customer Purchase Intent Using Logistic Regressio...

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2nd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Rajarajachozhan, C. Karthika, G. Rajakrishnammal, A. Mano, M. Kumar, P. Nithish Jayahari, E. Saveetha Engineering College Dept. of Electronics and Communication Engineering Tamil Nadu Chennai India Saveetha Engineering College Dept. of Artificial Intelligence and Data Science Tamil Nadu Chennai India Saveetha Engineering College Dept. of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331505745

Predicting customer purchase intent is crucial for modern businesses in order to improve engagement, refine marketing strategies, and increase revenue. Conventional rule-based systems encounter difficulties with dynamic and extensive customer data, limiting their flexibility and precision. This project employs a machine learning methodology utilizing logistic regression to forecast customer intent based on demographic, transactional, and behavioral data. The proposed model analyses input features including age, browsing history, and previous purchases, employing sophisticated data preprocessing methods such as One-Hot Encoding and feature scaling to guarantee data integrity. Through hyperparameter tuning and the assessment of critical metrics including accuracy, precision, recall, and Fl-score, the system provides dependable and actionable insights. Real-time predictive capabilities enable businesses to customize customer interactions, facilitating targeted marketing and enhancing customer experience. This project underscores the capacity of predictive analytics to tackle real-world issues, facilitating data-driven decision-making and sustainable business development. © 2025 IEEE.

关键词： Logistic regression

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Multispectral Images and IoT Based Tea Plantation Monitoring: A Proposed System Architecture 5

Multispectral Images and IoT Based Tea Plantation Monitoring...

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5th International Conference on Advanced Research in Computing, ICARC 2025

作者： Kariyawasam, K.P.W.D.V. Kahandagamage, P.N. Fernando, M.R.R. Fernandopulle, J.M. Jayasinghearachchi, Vishan Dissanayaka, Kapila Dept. of Software Engineering Sri Lanka Dept. of Information Technology Sri Lanka Dept. of Computer Science Sri Lanka

ISBN: (纸本)9798331530983

In recent years, the Sri Lankan tea industry has fallen behind its competitors in the global tea market. This decline is caused by the challenges in productivity and resource management due to the limitations of traditional crop monitoring methods. This study presents a prototype system architecture that integrates multispectral imagery and IoT technologies to enhance plantation monitoring. The proposed system uses drones to capture high-resolution multispectral images and IoT devices to collect real-time environmental data, providing a comprehensive approach to assessing plant yield and detecting stress. Built on a hexagonal architecture, the system emphasizes modularity, reliability, and scalability by ensuring a clear separation of core functionalities from external components. This design facilitates easy adaptation to various crop types and agricultural contexts, enabling flexibility in deployment and use. This flexible framework can serve as a blueprint for improving decision-making and management practices across diverse plantation environments. © 2025 IEEE.

关键词： Risk perception

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