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An efficient ACO-inspired multi-path routing for source location privacy with dynamic phantom node selection scheme in IoT environments

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Soft Computing 2024年第23期28卷 13149-13166页

作者： Arpitha, T. Chouhan, Dharamendra Shreyas, J. Department of Computer Science and Engineering University Visvesvaraya College of Engineering Bangalore University Karnataka Bengaluru560001 India Department of Information Technology Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Karnataka Manipal India

The rapid growth in the smart era of Internet of Things (IoT) relies on the various applications that lead to the design wide range of routing protocols utilizing Machine learning techniques. Third party interference in the open network to perform malicious activities by using location information of the node is high. Many researchers have designed a wide range of protocols to improve security and energy efficiency but the dynamic nature of the Internet of Things suppressed the performance of those algorithms. This may lead to data drop, node death, delay, less network lifetime, and increased third party malicious activities. In this paper, a novel routing mechanism is developed to preserve source location privacy and prevent adversaries from doing backtracking attacks and traffic analysis for energy preservation. The proposed model consists of two key functions Node/Network Condition based Dynamic Phantom Node selection (NCDPNS) and Ant colony optimization Algorithm Aided Multi-Path based Routing (ACOMPR). Here, NCDPNS selects the phantom node based on the node/network conditions like node availability, link availability, node energy level, distance from other nodes in the network, and number of neighboring hops to preserve the location privacy. ACOMPR selects the path based on the ant colony optimization algorithm to choose more than one path for data transmission with very less common resources shared among multiple paths between the source and destination for energy efficient data transmission. The proposed mechanism is achieving the source location privacy at the first stage and energy efficient routing at the second stage. The proposed mechanism is implemented using a Network Simulator-2 (NS2) simulator with predefined network parameters. The results depict that it achieves high throughput, less delay, increased network lifetime, and low energy dissipation for data transmission by preserving the location of the node. The dynamic nature of the IoT is considered

关键词： Ant colony optimization

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AdaPIP: Adaptive picture-in-picture guidance for 360° film watching

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Computational Visual Media 2024年第3期10卷 487-503页

作者： Yi-Xiao Li Guan Luo Yi-Ke Xu Yu He Fang-Lue Zhang Song-Hai Zhang Department of Computer Science and Technology Tsinghua UniversityBeijingChinaand Beijing National Research Center for Information Science and Technology(BNRist)Tsinghua UniversityBeijingChina Key Laboratory of Space Utilization Technology and Engineering Center for Space UtilizationChinese Academy of SciencesBeijingChina Victoria University of Wellington WellingtonNew Zealand

360°videos enable viewers to watch freely from different directions but inevitably prevent them from perceiving all the helpful *** mitigate this problem,picture-in-picture(PIP)guidance was proposed using preview windows to show regions of interest(ROIs)outside the current view *** identify several drawbacks of this representation and propose a new method for 360° film watching called *** enhances traditional PIP by adaptively arranging preview windows with changeable view ranges and *** addition,AdaPIP incorporates the advantage of arrow-based guidance by presenting circular windows with arrows attached to them to help users locate the corresponding ROIs more *** also adapted AdaPIP and Outside-In to HMD-based immersive virtual reality environments to demonstrate the usability of PIP-guided approaches beyond 2D *** user experiments on 2D screens,as well as in VR environments,indicate that AdaPIP is superior to alternative methods in terms of visual experiences while maintaining a comparable degree of immersion.

关键词： 360°videos picture-in-picture(PIP) virtual reality(VR) visual guidance

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Normalized category travel personality by considering explicit and implicit feedback (NCTP): approach for improving travel recommender systems search result

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International Journal of Information technology (Singapore) 2023年第7期15卷 3689-3708页

作者： Kumar, Niranjan Hanji, Bhagyashri R. Department of Computer Science and Engineering Global Academy of Technology Visvesvaraya Technological University Belagavi 590018 India Department of Computer Science and Engineering Dayananda Sagar Academy of Technology and Management Visvesvaraya Technological University Belagavi 590018 India

Large volumes of end-user-generated textual data are assembled every day which leads to the evolution of social media in the form of reviews/feedback, and brief description messages. As a consequence, end-user often see it difficult to understand more concerning the subject being discussed or appropriate knowledge from such material. The enormous amount of text-oriented data that is accessible via the online platform is analyzed using machine learning and natural language processing algorithms, including topic modeling techniques that have been more prevalent in current years. The novel approach is proposed to represent travel categories called the Normalized Category Travel Personality (NCTP). The main purpose of the technique is to construct the semantics of category feedback to model travelers’ interests to create the category travel personality (CTP) representation. Likewise, we normalize the CTP to obtain our proposed model. The NCTP category model will apprehend the explicit and implicit aspects of categories shown by the social-circle groups to find sentiment scores. The TripAdvisor dataset was considered to evaluate the performance of the NCTP model based on the topic-model quality, implicit and explicit characteristics, and some legacy statistical evaluation metrics, like Recall, Mean Average Precision, and Mean Reciprocal Rank. © 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of computer Applications and Management.

关键词： Probability distribution Rating and reviews Recommendation system Sentiment score

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Introduction to the Special Issue on Formal Methods and Models for System Design

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ACM Transactions on Embedded Computing Systems 2025年第3期24卷 1-3页

作者： Brandt, Jens Saha, Indranil Zhang, Lijun Hochschule Niederrhein Krefeld Germany Department of Computer Science and Engineering Indian Institute of Technology Kanpur Kanpur India State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China

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Klotski v2: Improved DNN Model Orchestration Framework for Dataflow Architecture Accelerators

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IEEE Transactions on computer-Aided Design of Integrated Circuits and Systems 2025年第3期44卷 1045-1058页

作者： Bai, Chen Wei, Xuechao Zhuo, Youwei Cai, Yi Zheng, Hongzhong Yu, Bei Xie, Yuan The Chinese University of Hong Kong Department of Computer Science and Engineering Hong Kong Hong Kong Alibaba DAMO Academy Computing Technology Laboratory Hangzhou311121 China Peking University School of Integrated Circuits Beijing100871 China The Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Hong Kong

Dataflow architecture accelerators are a new kind of scalable DNN accelerators. For an instruction, the availability of input operands solely determines the beginning of executions. DNN model orchestration determines how to partition, schedule, and map the computation to the underlying hardware. In this article, we propose the Klotski v2 framework to solve DNN model orchestration for dataflow architecture accelerators. First, a Bayesian optimization-based entropy-directed partition algorithm is proposed to transform a DNN model into μ ops. Second, a unified formal formulation for μ ops scheduling and mapping is presented. Third, a two-stage methodology is proposed to decouple the scheduling and mapping. Fourth, a Hilbert curve-based mapping heuristic is proposed to enhance problem-solving efficiency, improving the tradeoff between solution quality and algorithm runtime. Extensive results show that Klotski v2 can achieve an average of 21.57% higher execution performance improvement than the previous methodologies. With the Hilbert curve-based mapping heuristic, we improve the algorithm efficiency by an average of 63.50% across different DNN workloads. © 1982-2012 IEEE.

关键词： Scheduling algorithms

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Analysis of Prediction of Pneumonia from Chest X-ray images using CNN and Transfer Learning 5

Analysis of Prediction of Pneumonia from Chest X-ray images ...

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5th IEEE International Conference for Emerging technology, INCET 2024

作者： Vinay, K. Shashanka Kodipalli, Ashwini Swetha, P. Kumaraswamy, S. Dept. of Computer Science and Engineering Global Academy of Technology Karnataka Bengaluru India Dept of Artificial Intelligence and Data Science Global Academy of Technology Karnataka Bengaluru India

ISBN: (纸本)9798350361155

A good design for image classification problems is the CNN architecture you presented, which consists of 5 convolution blocks followed by 4 fully connected layers. From the input X-ray images, the convolutional blocks extract pertinent features, and the fully connected layers assist in determining the final classification based on those learned features. You have integrated various approaches to improve the performance of your model. The inputs to each layer are normalized through batch normalization, which can speed up training and enhance generalization. By removing certain neurons at random during training, dynamic dropout helps avoid overfitting. L2 regularization weight decay and learning rate decay are two efficient strategies for preventing overfitting and enhancing the model's capacity to expand to new data. Popular optimization algorithm Adam optimizer effectively neural network training. For binary classification problems like the diagnosis of pneumonia, the loss function for binary Cross-Entropy is the best option. To determine your model's efficacy, you must validate it using benchmark datasets that are available to the general public. You can evaluate your model's effectiveness by comparing its performance to that of current methods by conducting experimental investigations on these datasets. Your model performs well as evidenced by accuracy scores of 90.93%, 89.17% for multi-class classification and binary classification. tasks. Automated methods, such as the one you suggested, might help medical practitioners recognize pneumonia and spot diseased spots in chest X-ray pictures. However, it's crucial to remember that automated systems shouldn't take the place of professional radiologists' and doctors' skills and judgment;rather, they should be used as supportive tools. Medical To ensure accurate diagnosis and suitable patient care, specialists should always review and interpret the system's data. It's also crucial to take into account potential drawback

关键词： Convolutional neural networks

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Advancing Marine Species Detection: A Comparative Analysis of YOLOv5 and YOLOv8 in Challenging Underwater Environment 1

Advancing Marine Species Detection: A Comparative Analysis o...

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1st International Conference for Women in Computing, InCoWoCo 2024

作者： Bharath, R. Ujwal, H.U. Chandan, K. Ravindranath, R.C. Chandramma, R. Rakshith, H.R. Global Academy of Technology Department of Computer Science and Engineering Karnataka Bengaluru India Karnataka Bengaluru India

ISBN: (纸本)9798331518943

This work offers a thorough comparison of the YOLOv5 and YOLOv8 object detection algorithms with a focus on the identification and categorization of ten different marine species. To address the urgent demand for sophisticated computer vision solutions in marine biology, we assess these models' performance, paying particular attention to their accuracy and effectiveness in difficult underwater settings. The chosen marine species are diverse in terms of size, shape, and color, providing a strong baseline against which to evaluate the models' performance. The investigation and results provide light on the advantages and disadvantages of the models by carefully examining detection metrics, false positives, and false negatives. The study offers helpful advice for scholars and practitioners working in marine biology and other related fields by providing concrete suggestions for model selection based on observed performance. © 2024 IEEE.

关键词： Invertebrates

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Enhancing Early Detection of Pancreatic Cancer: A Machine Learning Approach with Explainable AI Insights

Enhancing Early Detection of Pancreatic Cancer: A Machine Le...

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2024 IEEE International Conference on computer Vision and Machine Intelligence, CVMI 2024

作者： Pattanashetti, Neeraj V Mayur, R. Prakash, Adarsh Adiga, Tryambaka B Kodipalli, Ashwini Rao, Trupthi Global Academy of Technology Dept. of Computer Science & Engineering Karnataka Bangalore India Global Academy of Technology Dept. of Information Science & Engineering Karnataka Bangalore India Global Academy of Technology Dept. of Artificial Intelligence & Data Science Karnataka Bangalore India

ISBN: (纸本)9798350376876

Among the most deadly and complex illnesses in the world, pancreatic cancer is typified by its early asymptomatic stage and subsequent discovery of the disease when it has progressed to an advanced stage. Getting the patients in a correct treatment path at the earliest point is important for suitable intervention and patient outcomes in the long run. We utilized advanced algorithms and model prediction techniques includes, feature extraction, hyperparameter tuning and explainability methods which aims to enhance both the comprehension and predictive accuracy of models employed. The goal is to assess patient health status and diagnose pancreatic diseases (cancer vs. non-cancer) by developing a learning algorithm. We obtained a dataset containing demographic information and urine biomarkers to start the investigation. First stage of our analysis employs a single classifier and later we apply bagging and boosting algorithms to achieve ensemble models. Hyperparameter fine-tuning has got a positive outcome, which has Gradient Boosting and Cat Boosting as its top performing models. The ensemble model produced excellent results (92.02 %), demonstrating the usefulness of the suggested approach. LIME and SHAP techniques play the key role in model outcome interpretability providing an insight of algorithmic decision-making process. Such a wide range of combinations of biomarkers have a potential of pancreatic cancer detection in early stages and thus will help shape diagnostics strategies in near future. © 2024 IEEE.

关键词： Diseases

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MetaReq: A Metadata Driven Strategic Semantics Oriented Model for Recommendation of Software Requirements 23th

MetaReq: A Metadata Driven Strategic Semantics Oriented Mode...

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23rd International Conference on Intelligent Systems Design and Applications, ISDA 2023

作者： Ramesh, Yukta Deepak, Gerard Department of Computer Science and Engineering Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Bengaluru India Department of Computer Science and Engineering BMS Institute of Technology and Management Yelahanka Bangalore India

ISBN: (纸本)9783031647789

There's a need for a semantics-oriented software requirement recom- mendation that encompasses knowledge and a strong classification ecosystem. The model uses preprocessing of the query words unto which entities from wiki data are harvested, which comprise World Wide Web knowledge. The model en- compasses strategies like classification of the dataset using decision tree classifiers and classification of the metadata using LSTM classifier. The encompassment of CoSim rank and Pielou's evenness index along with normalized pointwise mutual information (NPMI) measure create a semantics-oriented computation mechanism. The overall framework has the maximum mean precision, accuracy, recall, F-measure lowest value of FDR making it the best-in-class strategy for soft- ware requirement recommendation. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Semantics

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Dual-Mode Resonant Sectorial Monopole Antenna with Stable Backfire Gain

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Chinese Journal of Electronics 2024年第6期33卷 1478-1486页

作者： Feiyan JI Heng ZHANG Xiuqiong XING Wenjun LU Lei ZHU Jiangsu Key Laboratory of Wireless Communications Nanjing University of Posts and Telecommunications Key Laboratory of Wireless Sensor Network & Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau

A novel design approach to wideband, dual-mode resonant monopole antenna with stable, enhanced backfire gain is advanced. The sectorial monopole evolves from a linear, 0.75-wavelength electric prototype monopole under wideband dual-mode resonant operation. As theoretically predicted by the two resonant modes TE3/5,1and TE9/5,1within a 150° radiator, the operation principle is revealed at first. As have been numerically demonstrated and experimentally validated at 2.4-GHz band, the designed antenna exhibits a wide impedance bandwidth over 90.1%（i.e., 2.06–5.44 GHz）, in which the stable gain bandwidth in the backfire,-x-direction（θ = 90°, φ = 180°） with peak value of 3.2 dBi and fluctuation less than 3 dB is up to 45.3%（i.e., 3.74–5.44 GHz）. It is concluded that the stable wideband backfire gain frequency response should be owing to the high-order resonant mode in the unique sectorial monopole antennas.

关键词： Fluctuations Azimuth Prototypes Metals Resonance Frequency measurement Broadband antennas Impedance Gain Wideband

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