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26th International Conference on Distributed Computing and Networking, ICDCN 2025

作者： Das, Sajal K. Dhar, Amit Kumar Gorain, Barun Mahawar, Madhuri Department of Computer Science Missouri University of Science and Technology RollaMO United States Department of Computer Science and Engineering Indian Institute of Technology Bhilai Chhattisgarh Bhilai India

ISBN: (纸本)9798400710629

In this paper, we study collision-free graph exploration in an anonymous network. The network is modeled as a graph G = (V, E) where the nodes of the graph are unlabeled, and each edge incident to a node v has a unique label, called the port number, in {0, 1, ⋯, d - 1}, where d is the degree of the node v. Two identical mobile agents, starting from different nodes in G have to explore the nodes of G in such a way that for every node v in G, at least one mobile agent visits v and no two agents are in the same node in any round and stop. The time of exploration is the minimum round number by which both agents have terminated. The agents know the size of the graph but do not know its topology. If an agent arrives in the one-hop neighborhood of the other agent, both agents can detect the presence of the other agent but have no idea at which neighboring node the other agent resides. The agents may wake up in different rounds, but once awake, they execute a deterministic algorithm in synchronous rounds. An agent, after waking up, has no knowledge about the wake-up time of the other agent. The task of collision-free exploration is impossible to solve even for a line of length 2 where the agents are placed at the end nodes of the line and even if both agents wake up at the same time. We study the problem of collision-free exploration where some pebbles are placed by an Oracle at the nodes of the graph to assist the agents in achieving collision-free exploration. The Oracle knows the graph, the starting positions of the agents, and their wake-up schedule, and it places some pebbles that may be of different colors, at most one at each node. The number of different colors of the pebbles placed by the Oracle is called the color index of the corresponding pebble placement algorithm. The central question we study in this paper is: "What is the minimum number z such that there exists a collision-free exploration of a given graph with pebble placement of color index z?". For genera

关键词： Network theory (graphs)

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Artificial Humming Bird Optimization with Siamese Convolutional Neural Network Based Fruit Classification Model

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computer Systems science & engineering 2023年第11期47卷 1633-1650页

作者： T.Satyanarayana Murthy Kollati Vijaya Kumar Fayadh Alenezi E.Laxmi Lydia Gi-Cheon Park Hyoung-Kyu Song Gyanendra Prasad Joshi Hyeonjoon Moon Department of Information Technology Chaitanya Bharathi Institute of TechnologyHyderabadTelanganaIndia Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Electrical Engineering College of EngineeringJouf UniversitySakakaSaudi Arabia Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of International Affairs and Education Gangseo UniversitySeoul07661Korea Department of Information and Communication Engineering and Convergence Engineering for Intelligent Drone Sejong UniversitySeoul05006Korea Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea

Fruit classification utilizing a deep convolutional neural network(CNN)is the most promising application in personal computer vision(CV).Profound learning-related characterization made it possible to recognize fruits from ***,due to the similarity and complexity,fruit recognition becomes an issue for the stacked fruits on a weighing ***,Machine Learning(ML)methods have been used in fruit farming and agriculture and brought great convenience to human *** automated system related to ML could perform the fruit classifier and sorting tasks previously managed by human ***’s(convolutional neural networks)have attained incredible outcomes in image classifiers in several *** the success of transfer learning and CNNs in other image classifier issues,this study introduces an Artificial Humming Bird Optimization with Siamese Convolutional Neural Network based Fruit Classification(AMO-SCNNFC)*** the presented AMO-SCNNFC technique,image preprocessing is performed to enhance the contrast level of the *** addition,spiral optimization(SPO)with the VGG-16 model is utilized to derive feature *** fruit classification,AHO with end to end SCNN(ESCNN)model is applied to identify different classes of *** performance validation of the AMO-SCNNFC technique is tested using a dataset comprising diverse classes of fruit *** comparison studies reported improving the AMOSCNNFC technique over other approaches with higher accuracy of 99.88%.

关键词： Fruit classification computer vision machine learning deep learning metaheuristics

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Sentiment Analysis of Movie Reviews Using Machine Learning

Sentiment Analysis of Movie Reviews Using Machine Learning

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2025 International Conference on Pervasive Computational Technologies, ICPCT 2025

作者： Yadav, Avantika Garg, Payal Jain, Tarun Manipal University Department of Computer Science & Engineering Jaipur India Gl Bajaj Institute of Technology and Management Department of Computer Science & Engineering Greater Noida India

ISBN: (纸本)9798331508685

This paper delves into the critical role that machine learning plays in the accurate classification of sentiments expressed in movie reviews. Throughout the study we research and apply NLP using deep learning and machine learning algorithms to train and test our IMDb 50K movie reviews dataset on different models and feature embedding to compare their accuracies and choose the most optimal model for sentimental analysis. Ultimately, using deep neural network model BERT neural gives us the best accuracy of 94.2% compared to lexicon-based approaches due to the limitations in feature extractions like Bag of Words and TF-IDF. © 2025 IEEE.

关键词： Bag of Words BERT Deep Learning IMDb Dataset Machine Learning Natural Language Processin Sentiment Analysis TF-IDF Training and Testing

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Advancing Underwater Communication with NBO-MFO Hybrid Routing in UWSNs 10

Advancing Underwater Communication with NBO-MFO Hybrid Routi...

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10th International Conference on Communication and Signal Processing, ICCSP 2024

作者： Kalaiselvan, S.A. Kumar, M.Lenin Amanullah, M. Mani Chigurupati, T.R. Rajalakshmi Engineering College Department of Computer Science and Engineering Chennai India Vignan Institute of Technology and Science Department of Electronics and Communications Engineering Telangana India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Chennai India Tkr College of Engineering and Technology Department of Computer Science and Engineering Telangana India

ISBN: (纸本)9798350353068

In this research provides a solution for optimizing routing path selection in Underwater Wireless Sensor Networks (UWSNs). The algorithm combines Namib Beetle Optimization (NBO) and Moth-Flame Optimization (MFO), integrating them into the ILEACH methodology for efficient routing path selection. The algorithm operates in an iterative manner, commencing with NBO's feature selection process, evaluating fitness through average classification error and feature selection ratio. Simultaneously, MFO mimics moth behavior, updating positions via a logarithmic spiral function based on flame locations. The mutual learning phase facilitates information exchange between NBO and MFO, enhancing their collective intelligence and refining the routing path selection process. ILEACH's contribution lies in its fitness aggregation and selection methods. It amalgamates various criteria, including energy levels, distances, and node conditions, into a comprehensive fitness metric. Subsequently, ILEACH selectively identifies optimal routing paths aligned with energy-efficient criteria and node statuses, ensuring efficient data transmission and energy conservation within UWSNs. This integrated approach fosters a comprehensive strategy for routing path selection in UWSNs, ensuring sustainability and efficiency in data transmission within challenging underwater environments. © 2024 IEEE.

关键词： Iterative methods

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Improving ECAPA-TDNN Performance with Coordinate Attention

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Journal of Shanghai Jiaotong University (science) 2024年 1-7页

作者： Liu, Shuanghong Song, Zhida He, Liang School of Computer Science and Technology Xinjiang University Urumqi830017 China Xinjiang Key Laboratory of Signal Detection and Processing Urumqi830017 China Department of Electronic Engineering and Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China

The current mainstream networks, such as squeeze and excitation residual neural network (SE-ResNet) and emphasized channel attention, propagation and aggregation based time delay neural network (ECAPA-TDNN), enhance the capability of speaker embedding extractors to extract more discriminative speaker embeddings by incorporating squeeze and excitation (SE) attention within the convolutional blocks. However, the SE attention focuses solely on encoding inter-channel information, overlooking the importance of spatial positional information and time-frequency information, which are crucial for the model’s performance. In this paper, we first experimentally compare the effectiveness of several mainstream attention mechanisms in the computer vision domain for the ECAPA-TDNN model. Next, we focus on the substantial improvements that coordinate attention (CA) brings to the ECAPA-TDNN model. The introduction of CA can help the model embed time-frequency information into the channel representation. Even without using AS-Norm, our proposed model achieves relative reductions of about 5.3% equal error rate (EER) and 5.5% minimum detection cost function (minDCF) on both the Voxceleb-O and Voxceleb-H test sets compared to the ECAPA-TDNN baseline model. In addition, the EER is relatively reduced by 9.46% on the CN-Celeb1 test set. This result strongly demonstrates that the CA module can effectively improve the generalization ability of the ECAPA-TDNN model. © Shanghai Jiao Tong University 2024.

关键词： Neural network models

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Image based Android Malware Detection System using ResNet50 and VGG16 15

Image based Android Malware Detection System using ResNet50 ...

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15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Gundla, Rajeshwari Gengaje, Sachin R. Department of Computer Science & Engineering Walchand Institute of Technology Solapur India Department of Electronics and Computer Engineering Walchand Institute of Technology Solapur India

ISBN: (纸本)9798331300579

Attacks on mobile devices, such as smartphones and tablets, have increased as a result of their rising popularity. One of the most significant risks is mobile malware, which may lead to both security breaches and financial losses. Mobile malware will probably continue to develop and spread since it is used to commit different types of cybercrimes on mobile devices. As the Android operating system has gained popularity, mobile malware targets it especially. Users' security is seriously jeopardised by the quick spread of Android malware apps, which also makes it challenging to manually and statically analyse harmful files. Therefore, it is essential to accurately identify and categorise Android harmful files. There has been some discussion of Convolutional Neural Network (CNN) based approaches in this area, however there is still opportunity for performance enhancement. In this work, using two well-known deep learning models, ResNet-50 and VGG16, we present a transfer learning strategy to effectively detect the Android malware files. By converting malicious and benign APK files into grayscale images, the proposed model is trained on the AndroHealthCheck dataset. On the AndroHealthCheck dataset, our model outperforms state-of-the-art works in terms of accuracy, recall, precision, and F1 measures. © Grenze Scientific Society, 2024.

关键词： Android malware

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Adaptive Contrast Based Real-Time Image and Video Dehazing 5

Adaptive Contrast Based Real-Time Image and Video Dehazing

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5th International Conference on Circuits, Control, Communication and Computing, I4C 2024

作者： Joshi, Rohin Dange, Dhruv Kavya, K.S. Maiya, Sharath R Ramaiah Institute of Technology Department of Information Science and Engineering Bangalore India

ISBN: (纸本)9798331528539

Dehazing algorithms have been developed in re-sponse to the need for effectively and instantaneously removing atmospheric turbidities such as mist, haze, and fog from media. The removal of haze from an image or video enables the extraction of additional details from the scene. This paper presents the development of a real-time, memory-optimized dehazing system that utilizes digital image processing techniques and NVIDIA's CUDA architecture for efficient parallel computing. The methodology incorporates a quad-tree search algorithm for efficient atmospheric light estimation, which significantly enhances dehazing accuracy. Advanced contrast enhancement techniques are employed for transmission estimation to ensure clarity and visibility in dehazed images, addressing challenges such as non-uniform illumination and varying haze densities. For image restoration, the system dynamically clips values to improve brightness and minimize information loss. The transmission map's artifacts are then smoothed using a Gaussian filter, resulting in more reliable dehazing. Extensive testing on a variety of publicly accessible datasets demonstrated that the proposed model achieved comparable accuracy to numerous existing techniques, while also restoring high-quality dehazed images and videos. The system achieves a running time of 35ms per image and up to 10ms per frame for video sequences. Performance was objectively assessed using the Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM), yielding a PSNR of 28.75 and an SSIM of 0.80. © 2024 IEEE.

关键词： Image reconstruction

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Microplastics Detection in Freshwater Lakes Using Sentinel-1 Synthetic Aperture Radar Images 45

Microplastics Detection in Freshwater Lakes Using Sentinel-1...

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45th Asian Conference on Remote Sensing, ACRS 2024

作者： Agilan, B. Mithulesh, P. Kumar, Sourav N.R.S. Vani, K. Department of Information Science and Technology College of Engineering Chennai Guindy India

Microplastics in water bodies pose menacing threats to both aquatic ecosystems and human health once they infiltrate the food chain, it is imperative to devise an efficient methodology for detecting microplastics in water. This research endeavours to address a systematic approach to identify microplastics in inland water bodies using satellite imagery paired with deep learning. In-situ data mandatory for the study are mustered from open-source platforms like springeropen, containing coordinates of several water bodies and sampled data from particular dates. The pertinent Sentinel-1 Synthetic Aperture Radar data for dates mentioned in in-situ data are gathered. Obtained images are subjected to Lee's filter to handle the speckle noise present in them. In due course, a comprehensive dataset containing Vertical-Vertical + Vertical-Horizontal dual-polarisation data from Synthetic Aperture Radar images merged with corresponding in-situ data is created. The amalgamated dataset is utilised for training a multilayer perceptron model where the optimal hyperparameters are ascertained through executing Optuna, a hyperparameter optimization framework. Additionally, K-fold cross-validation is employed to assess the model performance in a robust manner exploring different subsets of the merged dataset. The trained multilayer perceptron model with the best possible hyperparameters scores a commendable R-squared value of 0.85, subsequently, the trained model is engaged in the production of inversion images for any designated target water body for whom Sentinel-1 Synthetic Aperture Radar images are obtainable representing the concentration of microplastics in them. Henceforth this study provides a formidable methodology for evaluating the existence and density of microplastic particles within inland water bodies safeguarding public health and paving the way for a sustainable environment. © 2024 45th Asian Conference on Remote Sensing, ACRS 2024. All rights reserved.

关键词： Radar imaging

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WSETO: wild stock exchange trading optimization algorithm enabled routing for NB-IoT tracking system

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International Journal of information technology (Singapore) 2024年第8期16卷 4895-4905页

作者： Sivadevuni, Sreeparnesh Sharma Naveen, J. Department of Computer Science and Engineering School of Engineering and Technology Christ University Karnataka Bangalore 560001 India

The Narrowband Internet of Things (NB-IoT) communication plays a significant role in the IoT due to the capability of generating broad exploration with the usage of limited power. Over the past few years, the Low Power Wide Area Networks (LPWAN) have been efficient in the data acquisition and remote monitoring area however they failed to generate high data rates, low latency, and the consumption of low power. To solve these problems, NB-IoT technology has developed in long-term asset tracking and it replaces the Global Positioning System (GPS) with its ubiquitous coverage. In this research, the Wild Stock Exchange Trading Optimization technique (WSETO) is proposed for a routing-based NB-IoT tracking system. The WSETO is the combination of the Wild Geese Algorithm (WGA) and SETO. By employing WSETO, the routing to the relevant target location is established effectively. The existing techniques like Low Power Asset Tracking of NB-IoT (LoPATraN), Monitoring system based on NB-IoT and BeiDou System/GPS (BDS/GPS), and Narrowband Physical Uplink Shared Channel (NPUSCH) are used to compare the WSETO approach. In rounds with a value of 2000, the WSETO demonstrates a superior location error of 0.001 in comparison to existing methods such as LoPATraN, a monitoring system utilizing NB-IoT and BDS/GPS, as well as NPUSCH. © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Global positioning system Low power wide area networks Narrowband internet of things Stock exchange trading optimization Wild geese algorithm

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Novel Design of UWB Jeans Based Textile Antenna for Body-Centric Communications

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computer Systems science & engineering 2022年第9期42卷 1079-1093页

作者： Mohammad Monirujjaman Khan Bright Yeboah-Akowuah Kaisarul Islam Eric Tutu Tchao Sumanta Bhattacharyya Rajesh Dey Mehedi Masud Fahad Alraddady Department of Electrical and Computer Engineering North South UniversityDhaka1229Bangladesh Department of Computer Engineering Kwame Nkrumah University of Science and TechnologyKumasiGhana Electronics and Communication Engineering Cambridge Institute of TechnologyRanchiIndia Department of Electronics and Communication Engineering Brainware Group of Institutions-SDETKolkataIndia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

This research presents an ultra-wideband (UWB) textile antenna designfor body-centric applications. The antenna is printed on a 1 mm thick denim substrate with a 1.7 relative permittivity. The jeans substrate is sandwiched between apartial ground plane and a radiating patch with a Q-shaped slot. The slotted radiating patch is placed above the substrate and measures 27.8 mm × 23.8 mm. In freespace, the antenna covers the ultra-wideband spectrum designated by the FederalCommunication Commission (FCC). Various parameters of the antenna designwere changed for further performance evaluation. Depending on the operating frequency, the antenna's realized gain varied from 2.7 to 5 dB. The antenna achievedhigh radiation efficiency with an omnidirectional radiation pattern. A parametricstudy was performed in research on varying antenna substrates and other components of the antenna. The three outermost layers of the human body are used tomodel a human phantom for on-body simulation. After that, the antenna wasplaced at five different distances from the phantom. The findings demonstrate thatat close distances to the phantom, the antenna's gain and efficiency at lower frequencies are reduced. The antenna's radiation efficiency and gain were muchhigher at higher frequencies for distances greater than 6 mm. Compared to freespace, the antenna's radiation pattern was more omnidirectional, especially athigher frequencies. This antenna is novel, compact and has an ultra wide bandwidth, a maximum of 94.60% radiation efficiency and a 5 dBi gain that will makeit a good candidate for body-centric communications.

关键词： Ultra-wideband body-centric communication on-body textile jeans slotted-patch WBAN

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