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computing, Networking, Telecommunications & Engineering sciences Applications (CoNTESA), International Conference on

作者： Suriya Sultana Israt Yasmin Muhammed J. A. Patwary Mohammad Arif Sobhan Bhuiyan Iftekhar Salam Mahdi H. Miraz Department of Computer Science and Engineering International Islamic University Chittagong School of Electrical and Electronic Engineering Xiamen University Malaysia Sepang Malaysia School of Computing and Data Science (SCDS) Xiamen University Malaysia Sepang Malaysia

Effective dermatological diagnosis and treatments significantly depend on the accurate categorisation of the skin lesions. It is difficult to classify skin lesions using automated diagnostic techniques due to class-imbalance datasets and the absence of labelled data. The applications of various deep learning methods have demonstrated superior performance in medical diagnosis in the recent past. Unfortunately, training these models requires a substantial quantity of labelled instances. A novel approach, combining Deep Learning convolutional neural networks (CNNs) as well as conditional generative adversarial networks (CGANs), for classifying skin lesion images, has been presented in this study. CGAN is an enhanced version of the GAN, in which the generator takes input images with specific class labels. Applying conditions for minority classes can help to equalise the dataset by increasing the sample size for those minority classes. In this research, CGANs were used to produce synthetic images of minority classes for a skin lesion dataset named PAD UFES-20. The images generated from CGANS were added then to the original dataset to train a lightweight deep-learning CNN network named MobileNetv2. The analysis of the results shows an improvement of 6% average accuracy and 5% recall value, when the synthetic data augmentation was added to the original dataset. This synthetic data augmentation approach can also widely be used in various medical classification applications to reduce the imbalance problems, resulting in enhanced diagnosis.

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Investigation of Traffic Radar Coverage Efficiency under Different Placement Strategies

Investigation of Traffic Radar Coverage Efficiency under Dif...

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International Conference on Internet of Things 2024, ICIoT 2024

作者： Yao, Shun Zhou, Jin Chieng, David Kwong, Chiew Foong Lee, Boon Giin Li, Jianqiang Chen, Yusen Next-Generation Internet of Everything Laboratory Department of Electrical and Electronic Engineering University of Nottingham Ningbo China Ningbo China School of Computer Science University of Nottingham Ningbo China Ningbo China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China Zhejiang Communication Investment Group Co. Ltd. Zhejiang China

This paper presents a comprehensive investigation of traffic radar coverage efficiency under different placement strategies in collaboration with Zhejiang Communications Investment Group Company Limited (CICO). The overall goal is to maximise coverage while minimising blind spots and the number of radars, given the constraints of the road. The NSGA-II multi-objective optimisation algorithm is found to be capable of generating a set of optimal solutions for the proposed radar placement configurations. When aiming for 100% coverage, the results indicate that a multi-antenna radar configuration requires the lowest radar density. Overall, this study provides valuable insights to transportation infrastructure owners in determining the best radar placement strategies for road traffic monitoring. © The Institution of Engineering & Technology 2024.

关键词： Multiobjective optimization

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Comparative Analysis of Prediction Models for Particulate Matter (PM2.5) Prediction 1

Comparative Analysis of Prediction Models for Particulate Ma...

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1st International Conference on Advances in Electrical, Electronics and Computational Intelligence, ICAEECI 2023

作者： Narkhede, Gaurav Hiwale, Anil S Pawar, Mangesh Dixit, Shagun Dr Vishwanath Karad MIT World Peace University School of Electronics and Communication Engieering Pune India Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India MIT College of Engineering Department of Electronics and Telecommunication Engieering Pune India

ISBN: (纸本)9798350342796

One of the key challenges with respect to the environment is the rise of concentration of pollutants in air, which needs to be addressed. For the prediction of pollutants, researchers have used a variety of cutting-edge machine learning prediction models. This study presents a comparative analysis of five alternative algorithms namely Multivariate LSTM, ET (Extra Tree), RF (Random Forest), LightGBM (Light Gradient Boosting Machine) and KNN (K-Nearest Neighbor) for prediction of pollutant PM2.5. In this work, the models are evaluated using the performance evaluation metrics such as MAE (Mean Absolute Error), RMSE (Root Mean Square Error), and MAPE (Mean Absolute Percent Error). The results show that all the models give less error but Multivariate LSTM model outperforms the other models. It is also observed that RH (Relative Humidity), PM10 and CO (Carbon Monoxide) are the important features in prediction of PM2.5 concentrations. © 2023 IEEE.

关键词： Extra Tree Regressor KNN LightGBM PM2.5Prediction Random Forest

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Graph Burning: Bounds and Hardness

arXiv

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arXiv 2024年

作者： Antony, Dhanyamol Das, Anita Gosavi, Shirish Jacob, Dalu Kulamarva, Shashanka Department of Computer Science and Automation Indian Institute of Science Bengaluru India School of Data Science Indian Institute of Science Education and Research Thiruvananthapuram India Department of Mathematics Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Manipal India Department of Mathematics Indian Institute of Technology Delhi India School of Informatics Kyoto University Kyoto Japan

For an undirected graph G, graph burning is defined as follows: at step t = 0 all vertices in G are unburned. At each step t ≥ 1, one new unburned vertex is selected to burn until we exhaust all the vertices. If a vertex is burned at step t, then all its unburned neighbors are burned in step t + 1, and the process continues until there are no unburned vertices in G. The burning number of a graph G, denoted by b(G), is the minimum number of steps required to burn all the vertices of G. The Burning Number problem asks whether the burning number of an input graph G is at most k or not. In this paper, we study the Burning Number problem both from an algorithmic and a structural point of view. The Burning Number problem is known to be NP-complete for trees with maximum degree at most three and interval graphs. Here, we prove that this problem is NP-complete even when restricted to connected cubic graphs and connected proper interval graphs. The well-known burning number conjecture asserts that all the vertices of a graph of order n can be burned in ⌈√n ⌉ steps. In line with this conjecture, upper and lower bounds of b(G) are well-studied for various graph classes. Here, we provide an improved upper bound for the burning number of connected Pk-free graphs and show that the bound is tight up to an additive constant 1. Finally, we study two variants of the problem, namely edge burning (only edges are burned) and total burning (both vertices and edges are burned). In particular, we establish their relationship with the burning number problem and evaluate the algorithmic complexity of these *** Codes 05C38, 05C05, 05C85 © 2024, CC BY.

关键词： Undirected graphs

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Dynamic capacity allocation of hybrid transportation units for cargo-hitching in urban public transportation systems

arXiv

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arXiv 2024年

作者： Bischoff, Paul Lienkamp, Benedikt Rambha, Tarun Schiffer, Maximilian School of Management Technical University of Munich Germany Department of Civil Engineering Center for Infrastructure Sustainable Transportation and Urban Planning Indian Institute of Science Bengaluru India Munich Data Science Institute Technical University of Munich Germany

To improve the utilization of public transportation systems (PTSs) during off-peak hours, we present an algorithmic framework that designs PTSs with hybrid transportation units (HTUs), which can transport passengers or freight by leveraging a flexible interior. Against this background, we study a capacitated network design problem to enable cargo-hitching in existing PTSs. Specifically, we study a setting with fixed vehicle routes and timetables in which vehicles can be equipped with HTUs to enable cargo-hitching. We optimize the network design from a total cost perspective to account for normalized network design costs tied to the investment in HTUs and freight routing costs. We present an algorithmic framework that encodes some of the problem’s constraints in a spatially and temporally expanded, layered graph, and solves the resulting network design problem with a price-and-branch algorithm. We apply this framework to a case study based on the subway network in the city of Munich. Our algorithm outscales commercial solvers by a factor of six and yields integer feasible solutions with a median integrality gap of less than 1.02% for all instances. We show that cargo-hitching with HTUs increases the utilization of PTSs, especially during off-peak hours, without cannibalizing passenger service level and quality. Moreover, we present a sensitivity analysis that indicates that cargo-hitching is worthwhile if truck-based transport occurs at an externality cost of more than 1.6 ∉ per vehicle and kilometer and loading and unloading costs of less than 2 ∉ per passenger equivalent. Copyright © 2024, The Authors. All rights reserved.

关键词： Sensitivity analysis

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A Study of Multimodal Identification Methods

A Study of Multimodal Identification Methods

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International Conference on Computer Network, Electronic and Automation (ICCNEA)

作者： Jianjian Feng Jianguo Wang School of Computer Science and Engineering Xi'an Technological University Xi’an China Research Institute of Artificial Intelligence and Data Science Xi'an Technological University Xi’an China

The purpose of this paper is to investigate unimodal determination and decision layer fusion methods in multimodal face recognition and to evaluate the effectiveness of decision layer fusion. Experiments are conducted on the "VidTIMIT" and "MOBIO" datasets using convolutional neural networks and MFCC feature extraction techniques. The performance of three feature fusion methods, front-end fusion, intermediate fusion and decision layer fusion, is compared. The experimental results show that the recognition accuracies are 94.9%, 94.7% and 94%, 94.1% for the face and voice models only, respectively. However, the accuracy decreases slightly in the case of front-end fusion. The best accuracy was achieved when the decision layer fusion method was used, reaching 95.7% and 95.6%, respectively. This indicates that training face and voice print data separately and fusing classifier output scores can effectively improve face recognition accuracy. This study explores feature fusion methods in the field of multimodal face recognition and experimentally demonstrates the advantages of decision layer fusion in improving accuracy, pointing to a new direction for future research.

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Using Continuous Integration (CI) For Managing Programming Assignments --- Conference Tutorial

Journal of Computing Sciences in Colleges

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Journal of computing sciences in Colleges 2024年第8期39卷

作者： Sunjae Park School of Computing and Data Science Wentworth Institute of Technology Boston

In this tutorial, instructors will be able to learn how to work with various tools on setting up a Continuous Integration Pipeline (CI pipeline), to automatically verify their programming assignments are valid. This t...

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Five-user quantum virtual local area network with an AlGaAs entangled photon source

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science China(Physics,Mechanics & Astronomy) 2025年第3期68卷 61-73页

作者： Cheng Qian Hongkai Tian Xu Jing Yichen Liu Zhe Chen Huiran Luo Yuan Du Xiaodong Zheng Tangsheng Chen Yuechan Kong Hua-Lei Yin Dong Jiang Bin Niu Liangliang Lu Key Laboratory of State Manipulation and Advanced Materials in Provincial Universities School of Physical Science and TechnologyNanjing Normal UniversityNanjing210023China School of Internet Anhui UniversityHefei230039China National Key Laboratory of Solid-State Microwave Devices and Circuits Nanjing Chip Valley Industrial Technology InstituteNanjing Electronic Devices InstituteNanjing210016China Research Center for Quantum Optics and Quantum Communication School of ScienceQingdao University of TechnologyQingdao266520China Department of Physics and Beijing Key Laboratory of Opto-electronic Functional Materials and Micro-nano Devices Key Laboratory of Quantum State Construction and Manipulation(Ministry of Education)Renmin University of ChinaBeijing100872China Beijing Academy of Quantum Information Sciences Beijing100193China National Engineering Research Center of Agro-Ecological Big Data Analysis and Application Anhui UniversityHefei230601China National Laboratory of Solid-State Microstructures and School of Physics Nanjing UniversityNanjing210093China Hefei National Laboratory Hefei230088China

The promotion of quantum network applications demands the scalable connection of quantum *** is preferable to set up multiple logical networks coexisting on a single physical network infrastructure to accommodate a larger number of *** we present a quantum virtual network architecture that offers this level of scalability,without being constrained to a fixed physical-layer network relying solely on passive multiplexing *** architecture can be understood as arising from the superposition of a fully connected entanglement distribution network and port-based virtual local area network,which group multiusers by access *** terms of hardware,we leverage a semiconductor chip with a high figure-of-merit modal overlap to directly generate high-quality polarization entanglement,and a streamlined polarization analysis module,which requires only one single-photon detector for each end *** experimentally perform the BBM92 QKD protocol on the five-user quantum virtual network and demonstrate voice and image encryption on a campus area *** results may provide insights into the realization of large-scale quantum networks with integrated and cost-efficient photonic architecture.

关键词： quantum network quantum entanglement distribution integrated photonics image and voice encryption

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Correlation and interaction between temperature and freeze-thaw in representative regions of Antarctica

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International Journal of Digital Earth 2022年第1期15卷 2296-2318页

作者： Dong Liang Huadong Guo Qing Cheng Lu Zhang Lingyi Kong Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijingPeople’s Republic of China University of Chinese Academy of Sciences BeijingPeople’s Republic of China International Research Center of Big Data for Sustainable Development Goals BeijingPeople’s Republic of China School of Computer Science China University of GeoscienceWuhanPeople’s Republic of China

As the most sensitive and direct indicator of global climate change,the freezing and thawing of the Antarctic ice sheet is of great significance for research on surface mass and energy *** this study,four representative regions in Antarctica were selected and correlation analysis,Granger causality testing,and cluster analysis were applied to comprehensively analyze the correlation and response of spatiotemporal variation in freeze-thaw and *** conclusions are as follows.(1)In the Antarctic Peninsula,a phenomenon was demonstrated that the summer shifts *** December and colder March temperatures were observed in the Amery Ice Shelf and Queen Maud Land.(2)The Antarctic Peninsula featured the most severe degree of melting among the four regions,with the largest melt area in the past 30 years appearing during the 2015/2016 ***,the number of melt days in most areas of the Antarctic Peninsula was observed to have decreased.(3)There is a strong correlation between the freeze-thaw state of the Antarctic ice sheet and temperature,as well as spatial differences among regions,but the data were clustered at different time scales.

关键词： Antarctic ice sheet Big Earth data freeze-thaw microwave remote sensing snowmelt temperature

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Dynamic Lane Management with IoT for Real-time Lane Configuration and Traffic Flow 2

Dynamic Lane Management with IoT for Real-time Lane Configur...

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2nd International Conference on Computer, Communication and Control, IC4 2024

作者： Pasha, Mohammed Rehaman Latha, S. Usha, R. Marin, V. Bini Ishwarya, M.V. Muthulekshmi, M. Malla Reddy Institute of Engineering and Technology Department of Computer Science and Engineering Telangana Hyderabad India Department of Department of Biotechnology Tamil Nadu Salem India S. A. Engineering College Department of Mathematics Tamil Nadu Chennai India Srm Institute of Science and Technology Faculty of Management Studies Tamil Nadu Ramapuram Chennai India Agni College of Technology Artificial Intelligence and Data Science Department Tamil Nadu Thazhambur India Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Biomedical Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350387933

Traffic may be reduced and transportation efficiency improved by properly controlling traffic flow in urban areas. This research provides a new method for managing lanes in real-time by using IoT connectivity. To optimize traffic flow in response to shifting demand patterns, the suggested system prioritizes making lane design changes in real time depending on the current traffic conditions. Using information collected from Internet of Things (IoT) sensors and linked automobiles, the system may dynamically allot lanes in response to variations in traffic volumes and congestion. It describes developing and deploying a dynamic lane control system based on the Internet of Things, stressing the technology's potential to improve traffic flow in congested metropolitan areas. The simulation results show its efficiency in decreasing traffic and increasing throughput. It demonstrates the potential of intelligent transportation systems for creating smarter and more efficient cities by combining IoT, real-time data processing, and traffic control. © 2024 IEEE.

关键词： Internet of things

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