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Detection of Lung Cancer using CNN- ZF NET 1

Detection of Lung Cancer using CNN- ZF NET

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1st International Conference on computer, Power and Communications, ICCPC 2022

作者： Devi, D. Muruga Radha Jancy, P. Leela Tamilselvi, P. Logeswaran, S. Vigneshwaran, E. Jeyachandran, A. Sri Sai Ram Institute of Technology Department of Information Technology Chennai India Rajalakshmi Engineering College Department of Computer and Business System Chennai India

ISBN: (纸本)9798350397840

Prevalence of Lung cancer is one of the most important categories among the various types of cancers. The basic step in the prediction of Lung Cancer is sampling of CT/MRI scan images of Lungs. An expert in that field must do thorough analysis in the detection of carcinoma in patients. Hence, there is a need for an efficient system that is capable of identifying lung cancer from multiple datasets. This ensures the condition of Cancer by observing the size of tumor and location of tumor. In our method detection of Lung cancer is performed using ZF NET Convolutional Neural Network (CNN) and in the process of machine learning we have used the pre-processed dataset from Kaggle and training, validation, and testing are done appropriately to obtain accuracy of 80% and above. © 2022 IEEE.

关键词： Convolutional neural networks

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MMM-RS: A Multi-modal, Multi-GSD, Multi-scene Remote Sensing Dataset and Benchmark for Text-to-Image Generation 38

MMM-RS: A Multi-modal, Multi-GSD, Multi-scene Remote Sensing...

引用

38th Conference on Neural information Processing systems, NeurIPS 2024

作者： Luo, Jialin Wang, Yuanzhi Gu, Ziqi Qiu, Yide Yao, Shuaizhen Wang, Fuyun Xu, Chunyan Zhang, Wenhua Wang, Dan Cui, Zhen PCA Lab Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China Beijing Institute of Spacecraft System Engineering Beijing China

Recently, the diffusion-based generative paradigm has achieved impressive general image generation capabilities with text prompts due to its accurate distribution modeling and stable training process. However, generating diverse remote sensing (RS) images that are tremendously different from general images in terms of scale and perspective remains a formidable challenge due to the lack of a comprehensive remote sensing image generation dataset with various modalities, ground sample distances (GSD), and scenes. In this paper, we propose a Multi-modal, MultiGSD, Multi-scene Remote Sensing (MMM-RS) dataset and benchmark for text-to-image generation in diverse remote sensing scenarios. Specifically, we first collect nine publicly available RS datasets and conduct standardization for all samples. To bridge RS images to textual semantic information, we utilize a large-scale pretrained vision-language model to automatically output text prompts and perform hand-crafted rectification, resulting in information-rich text-image pairs (including multi-modal images). In particular, we design some methods to obtain the images with different GSD and various environments (e.g., low-light, foggy) in a single sample. With extensive manual screening and refining annotations, we ultimately obtain a MMM-RS dataset that comprises approximately 2.1 million text-image pairs. Extensive experimental results verify that our proposed MMM-RS dataset allows off-the-shelf diffusion models to generate diverse RS images across various modalities, scenes, weather conditions, and GSD. The dataset is available at https://***/ljl5261/MMM-RS. © 2024 Neural information processing systems foundation. All rights reserved.

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Affinity-Based Power Flow Optimization in Reconfigurable Picogrid

Affinity-Based Power Flow Optimization in Reconfigurable Pic...

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2024 IEEE/SICE International Symposium on system Integration, SII 2024

作者： Kokubu, Ryota Oeda, Kaito Kawakita, Yuusuke Yokogawa, Shinji Tobe, Yoshito Ichikawa, Haruhisa Graduate School of Science and Engineering Aoyama Gakuin University Sagamihara Japan Kanagawa Institute of Technology Department of Information and Computer Sciences Atsugi Japan Info-Powered Energy System Research Center The University of Electro-Communications Chofu Japan

ISBN: (纸本)9798350312072

In recent years, there has been an increasing demand to adopt renewable energy resources to power grids for environmental issues and energy concerns. A virtual grid system, which is designed to utilize decentralized resources, is proposed as an approach. This system enables users to construct their power grids with virtual grid hubs (VG Hub) which interconnect via commercially available cables according to USB Power Delivery (USB PD). A prototype of VG Hub is capable of synthesizing and distributing DC power for connected devices, and the power flow control is managed by a microcontroller. Our previous study proposed a method called Minimum-Hop Power Path Routing (MHPPR). This method determines the power flow that uses the closest source in candidates which can fulfill the demand when a load connects to the network to minimize power loss due to transmission. However, this could result in unproductive power flow, such as a flow that consumes power stored in batteries prior to surplus power from generators. Therefore, we assumed that there are factors to value a source for a load other than demand and supply capacity, and inferred that the factor derives from the type of device. We defined this factor as the affinity between devices. The objective of this study is to solve the power path optimization problem while taking affinity into account. In this study, we discussed device classification and affinity between types and defined affinity coefficients. We then extended MHPPR by incorporating this affinity coefficient. The results have shown that the proposed method selected the sources following the priority defined by the affinity. © 2024 IEEE.

关键词： Renewable energy

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FaRo-PPF: Fast and Robust Point Pair Feature for 6D Pose Estimation in Industrial Stamping 8

FaRo-PPF: Fast and Robust Point Pair Feature for 6D Pose Est...

引用

8th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： He, Cheng Zhang, Xuebo Zhao, Zhenjie Institute of Robotics and Automatic Information System College of Artificial Intelligence Nankai University Tianjin Key Laboratory of Intelligent Robotics Tianjin300350 China School of Computer Science Nanjing University of Information Science and Technology Nanjing210044 China

ISBN: (纸本)9798350300178

Estimating 6D poses of targets efficiently is critical for industrial stamping tasks, in which the Point Pair Feature (PPF) method has been widely used. Based on PPF, this paper proposes Fast and Robust PPF, i.e. FaRo-PPF, which improves PPF in the following three key aspects: adaptive down-sampling based on surface features, point pair matching based on voting ball, and normal-based pose verification. The three designs alleviate existing problems of the local matching stage in PPF, and make FaRo-PPF a stronger method of 6D pose estimation in industrial stamping. To demonstrate the effectiveness of FaRo-PPF, we compare it with PPF on five publically available datasets. Experiment results showed that FaRo-PPF is able to significantly improve accuracy by about 15% and reduce the execution time by about 40% across all test data. We further conduct a grasping and assembly experiment on a physical robot arm, and similar improvement can be observed. FaRo-PPF achieves a higher success rate of assembly and reduces the execution time by about 50%. © 2023 IEEE.

关键词： Stamping

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The Implications of Electronics Money on the Digital Payment Method 6th

The Implications of Electronics Money on the Digital Payment...

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6th International Conference on Intelligent Sustainable systems, ICISS 2023

作者： Rahmadiyanti, Aulia Sisca Kamilah, Ghina Hanifah, Salma Nurul Gaol, Ford Lumban Matsuo, Tokuro School of Information System Bina Nusantara University Alam Sutera Indonesia Computer Science Department Bina Nusantara University Jakarta11480 Indonesia Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (纸本)9789819917259

Nowadays, as a result of globalization’s impact and the fast growth of technology, it is unquestionably beneficial to our everyday activities. Developed technology enables a plethora of new conveniences not before available. Because increasingly advanced technology encourages individuals to conduct all transactions digitally and is simple to use, payment systems based on electronic money have emerged and are often utilized for daily transactions. These technical advancements also have an effect on the community’s lifestyle and payment systems, since they enable the replacement of cash payments with more efficient and convenient electronic payment systems based on electronic money (e-money). The purpose of this research is to ascertain the consequences of utilizing electronic money as a contemporary payment mechanism that is often utilized by individuals for purchasing and selling activities. Electronic money is similar to currency in that it may be carried and stored anywhere. The usage of simple to use electronic money is anticipated to improve consumers’ transactional convenience and may continue to be the community’s preferred payment transaction instrument in the digital era. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Electronic money

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Mining Road Traffic Accident Data for Prediction of Accident Severity

Mining Road Traffic Accident Data for Prediction of Accident...

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2023 International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2023

作者： Bahiru, Tadesse Kebede Manjula, V.S. Akele, Tadesse Birara Tesfaw, Engdaw Ayalew Belay, Tadesse Destaw Kombolcha Institute of Technology Wollo University College of Informatics Dept. of Information Technology Amhara Kombolcha Ethiopia Kombolcha Institute of Technology Wollo University College of Informatics Pg Dept of Computer Science Amhara Kombolcha Ethiopia Kombolcha Institute of Technology Wollo University College of Informatics Dept. of Information System Amhara Kombolcha Ethiopia Wachamo University School of Computing and Informatics College of Engineering and Technology Dept. of Information Technology SSNPR Hosaena Ethiopia

ISBN: (纸本)9781665474511

As World Health Organization reports show more than 1.3 million people die each year from traffic accidents and more than twenty to fifty million people are harmed by non-fatal accidents. Understanding and identifying the major factors of road traffic accidents can help the stakeholders to take appropriate measures to minimize the accidents. Support Vector Machine (SVM), J48, and Naïve Bayes (NB) classification techniques are implemented to build a model that predicts accident severities and to identify road traffic accident factors. As experimental findings showed weather conditions, number of lanes, road lighting conditions, and speed limit are the determinant factors that cause more accident severity. Finally, the classification and prediction performance of the models are compared using various performance evaluation techniques. J48 classifier has better classification performance than Support Vector Machine and Naïve Bayes classifiers. Naïve Bayes is the classifier that showed the lowest performance than others, but it has good performance in classifying fatal accident severities rather than serious and slight accident severities. © 2023 IEEE.

关键词： Support vector machines

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A third-party platoon coordination service: Pricing under government subsidies

A third-party platoon coordination service: Pricing under go...

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作者： Bai, Ting Johansson, Alexander Li, Shaoyuan Johansson, Karl Henrik Mårtensson, Jonas School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden KTH Royal Institute of Technology Stockholm Sweden Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China Digital Futures Stockholm Sweden

This paper models a platooning system consisting of trucks and a third-party service provider (TPSP), which performs platoon coordination, distributes the platooning profit in platoons, and charges trucks in exchange for the services. Government subsidies used to incentivize platooning are also considered. We propose a pricing rule for the TPSP, which keeps part of the platooning profit including the subsidy each time a platoon is formed. In addition, a platoon coordination solution based on the distributed model predictive control (MPC) is proposed, in which the pricing rule under government subsidies is integrated. We perform a realistic simulation over the Swedish road network to evaluate the impact of the pricing rule and subsidies on the achieved profits and fuel savings. Our results show that subsidies are an effective mean to boost fuel savings from platooning. Moreover, the simulation study indicates that high pricing corresponds to a low platooning rate of the system, as trucks' incentives for platooning decrease. © 2023 The Authors. Asian Journal of Control published by John Wiley & Sons Australia, Ltd on behalf of Chinese Automatic Control Society.

关键词： Trucks

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Use of E-Wallet as a Substitute for Physical Money in Transactions at Malls 4th

Use of E-Wallet as a Substitute for Physical Money in Transa...

引用

4th International Conference on Inventive Computation and information Technologies, ICICIT 2022

作者： Kurniawan, Achmad Rizky Imam, Rafif Zhalifunnas, Rifqi Farhan Putra, Armando Rama Gaol, Ford Lumban Matsuo, Tokuro School of Information System Bina Nusantara University Alam Sutera Jakarta Indonesia Binus Graduate Program—Doctor of Computer Science Jakarta Indonesia Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (纸本)9789811974014

Several challenges have emerged as a result of the rapid spread of Covid-19 in Indonesia. To combat the pandemic, the government has also issued general guidelines for avoiding/limiting direct contact with common people who do not live with them. However, in some unavoidable cases, such as cash transactions, the social distancing has not yet been followed properly. These type of challenges can be avoided by the introduction of e-wallets and e-money. This research study examines the transactions made using e-wallets and e-money and how these methods are increasing sales in public places. The proposed research study has attempted to utilize both qualitative and a quantitative method to observe the customer behavior while using e-wallet as a substitute for physical money when making a transaction in a shopping mall. The result of the proposed research work will be compared with the existing literature to provide a conclusion based on existing research data and literature. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Electronic money

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Effective Heart Attack Prediction method using Machine Learning Algorithm

Effective Heart Attack Prediction method using Machine Learn...

引用

International Conference on Communications and Signal Processing

作者： M.G. Chitra Ramya Govindaraj School of Computer Science Engineering and Information System (SCORE) Vellore Institute of Technology Vellore TN India

ISBN: (数字)9798350353068

ISBN: (纸本)9798350353075

In today’s era development cardiovascular disease is the most common disease that cause a heart attack. So, diagnosing heart disease patients on time is the most challenging task in the medical field. Due to expensive treatment the poor people prohibit to take over heart disease treatment. The cardiologist’s doctors generally predict the patient’s heart attack with the help of a scrutinized patient report, electrocardiography, blood tests, computer report based on the patient’s previous database before seriousness of patient diseases. This study aims to analyze different machine learning (ML) algorithms that are currently available for predicting heart attacks, including decision trees, Random Forest, XGBoost, K-Nearest Neighbors, Support Vector Machines, and Logistic Regression. Finally, we obtained the best algorithm from this existing work based on accuracy, precision and recall.

关键词： Support vector machines Heart Machine learning algorithms Signal processing algorithms Cardiac arrest Predictive models Prediction algorithms

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Scavenger: Better Space-Time Trade-Offs for Key-Value Separated LSM-trees 40

Scavenger: Better Space-Time Trade-Offs for Key-Value Separa...

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40th IEEE International Conference on Data engineering, ICDE 2024

作者： Zhang, Jianshun Wang, Fang Qiu, Sheng Wang, Yi Ou, Jiaxin Huang, Junxun Li, Baoquan Fang, Peng Feng, Dan School of Computer Science and Technology Huazhong University of Science and Technology Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Engineering Research Center of Data Storage Systems and Technology Ministry of Education of China China Shenzhen Huazhong University of Science and Technology Research Institute China Bytefrance Inc.

ISBN: (纸本)9798350317152

Key-Value Stores (KVS) implemented with log-structured merge-tree (LSM-tree) have gained widespread ac-ceptance in storage systems. Nonetheless, a significant challenge arises in the form of high write amplification due to the compaction process. While KV-separated LSM-trees successfully tackle this issue, they also bring about substantial space am-plification problems, a concern that cannot be overlooked in cost-sensitive scenarios. Garbage collection (GC) holds significant promise for space amplification reduction, yet existing GC strategies often fall short in optimization performance, lacking thorough consideration of workload characteristics. Additionally, current KV-separated LSM-trees also ignore the adverse effect of the space amplification in the index LSM-tree. In this paper, we systematically analyze the sources of space amplification of KV-separated LSM-trees and introduce Scavenger, which achieves a better trade-off between performance and space amplification. Scavenger initially proposes an I/O-efficient garbage collection scheme to reduce I/O overhead and incorporates a space-aware compaction strategy based on compensated size to minimize the space amplification of index LSM-trees. Extensive experiments show that Scavenger significantly improves write performance and achieves lower space amplification than other KV-separated LSM-trees (including BlobDB, Titan, and TerarkDB). © 2024 IEEE.

关键词： Economic and social effects

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