检索结果-内蒙古大学图书馆

Time-series satellite remote sensing reveals gradually increasing war damage in the Gaza Strip

National science Review 2024年第9期11卷 181-191页

作者： Shimaa Holail Tamer Saleh Xiongwu Xiao Jing Xiao Gui-Song Xia Zhenfeng Shao Mi Wang Jianya Gong Deren Li State Key Laboratoryof Information Engineering in Surveying Mapping and Remote SensingWuhan University Geomatics Engineering Department Faculty of Engineering at Shoubra Benha University School of Computer Science Wuhan University Collaborative Innovation Center of Geospatial Technology National Engineering Research Center for Multi-media Software Institute of Artificial IntelligenceWuhan University

War-related urban destruction is a significant global concern, impacting national security, social stability,people's survival and economic development. The effects of urban geomorphology and complex geological contexts during conflicts, characterized by different levels of structural damage, are not yet fully understood globally. Here we report how integrating deep learning with data from the independently developed Luo Jia3-01 satellite enables near real-time detection of explosions and assessment of different building damage levels in the Israel–Palestine conflict. We found that the damage continually increased from 17 October 2023 to 2 March 2024. We found 3747 missile craters with precision positions and sizes, and timing on vital infrastructure across five governorates in the Gaza Strip on 2 March 2024, providing accurate estimates of potential unexploded ordnance locations and assisting in demining and chemical decontamination. Our findings reveal a significant increase in damage to residential and educational structures, accounting for 58.4% of the total—15.4% destroyed, 18.7% severely damaged, 11.8% moderately damaged and 12.5% slightly damaged—which exacerbates the housing crisis and potential population displacement. Additionally, there is a 34.1% decline in the cultivated area of agricultural land, posing a risk to food security. The Luo Jia3-01 satellite data are crucial for impartial conflict monitoring, and our innovative methodology offers a cost-effective, scalable approach to assess future conflicts in various global *** first-time findings highlight the urgent need for an immediate ceasefire to prevent further damage and support the release of hostages and subsequent reconstruction efforts.

关键词： war damage monitoring satellite remote sensing missile crater detection type of damaged building building damage level detection Gaza Strip

来源：评论

学校读者我要写书评

暂无评论

Timo: In-memory temporal query processing for big temporal data

Timo: In-memory temporal query processing for big temporal d...

引用

作者： Zheng, Xiao Liu, Houkai Wang, Xiujun Wu, Xuangou Yu, Feng School of Computer Science and Technology Anhui University of Technology Maanshan China Institute for Artificial Intelligence Hefei Comprehensive National Science Center Hefei China Anhui Engineering Laboratory for Intelligent Applications and Security of Industrial Internet Anhui University of Technology Anhui Maanshan China School of Computer Science and Engineering & School of Software Guangxi Normal University Guilin China Key Laboratory of Computer Network and Information Integration Southeast University Nanjing China

Today's internet applications generate massive temporal data anywhere and anytime. Although some disk-based temporal systems are currently available, they suffer from poor I/O performance, especially when applied in intelligent applications deployed in the cloud and edge environments. Therefore, how to process temporal operations with low latency and high throughput becomes a crucial problem for efficient data processing. This paper proposes Timo, a distributed in-memory temporal query and analytic model for big temporal data. Firstly, a space-efficient temporal index is proposed to support more efficiently query performance with less memory space than the state-of-art methods. Secondly, based on the temporal locality feature of temporal queries, Timo proposes a partitioner mechanism, which utilizes forward scan algorithm, to improve query throughput. Thirdly, some optimal strategies are proposed to improve the execution process of temporal query and analysis, which reduce intermediate result data size and improve the throughput much further. Lastly, we implement the Timo system on the Apache Spark platform, which extends Spark dataset API with temporal query and analysis API functions for users. Extensive experimental results show that the Timo system outperforms other Spark-based temporal systems in terms of both query latency and throughput. © 2021 John Wiley & Sons, Ltd.

关键词： Data handling

来源：评论

学校读者我要写书评

暂无评论

Identification of Diabetic Related Eye Diseases Using Deep Learning

Identification of Diabetic Related Eye Diseases Using Deep L...

引用

Advancements in Computing (ICAC), International Conference on

作者： Wijesinghe. K.H Dilshan U.K.T Dilshan K.B.G.L Tharupathi M.A.U Sanvitha Kasthuriarachchi Samantha Rajapaksha Department of Computer Science and Software Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Sri Lanka Institute of Information Technology Malabe Sri Lanka

Visual disability seems to be increasing and widespread worldwide. Current diagnostics require manual expertise for diagnosis. The advancement of Artificial Intelligence research for medical applications has been in focus in recent years. Fundus images and oct images are valuable sources of information to help ophthalmologists diagnose vision disorders or eye diseases. Early detection can improve the chances of recovery and prevent blindness. The application of an intelligent computer-based approach to classifying different eye disorders is extremely beneficial for both diagnosis and prevention. The proposed expert system for diagnosing diabetic macular edema, diabetic retinopathy, cataracts, and glaucoma diseases is discussed in this research study. It is based on deep learning image processing techniques. For the detection of eye diseases, software used retinal and OTC images. This study presents Yolo, UNET, customized CNN, and Auto ML model-based system for detecting eye diseases. For the tasks of disease identification and grading, the suggested methods each obtained more than 87% accuracy. The primary objective of this study is to achieve automated identification of eye disease images. This is accomplished through the implementation of a deep learning model alongside advanced image processing techniques, enabling the automatic classification of eyes into either a healthy or diseased category.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Hybrid Power Generation Forecasting Using an Intellectual Evolutionary Energy-Preserve Rate Clustering Technique 1

引用

10th International Conference on Innovations in computer science and engineering, ICICSE 2022

作者： Webber, Julian L. Jayagopal, Vellingiri Mehbodniya, Abolfazl Sengan, Sudhakar Velayutham, Priya Rangasamy, Rajasekar Stalin David, D. Doha Kuwait Department of Software & System Engineering School of Information Technology & Engineering Vellore Institute of Technology Tamil Nadu Vellore632014 India Department of Computer Science and Engineering PSN College of Engineering and Technology Tamil Nadu Tirunelveli627152 India Department of Computer Science and Engineering Paavai Engineering College Tamil Nadu Namakkal637018 India Department of Computer Science and Engineering GITAM School of Technology GITAM University Karnataka Bengaluru561203 India Department of Information Technology Vel Tech Multi Tech Dr.Rangarajan Dr.Sakunthala Engineering College Tamil Nadu Chennai600072 India

ISBN: (数字)9789811974557

ISBN: (纸本)9789811974540

The significant growth of Wind Power (WP) has significant challenges due to the inconsistency and uncertainty of Wind Power Generation (WPG) to ensure the power system. Solar energy and WP calculation are great ways to overcome the problem. Mainly voltage and frequency fluctuations and harmonics have a high impact on the power generation and distribution system;in any high case, the power quality of grid systems is reduced. This can be primarily solved with proper design, advanced rapid response control facilities and optimization of power systems. A new type of Multi-term Wind Energy (WE) with an IEEE 30 bus forecasting system based on digital weather forecasting and error modification methods is presented. From the Evolutionary Energy- Preserve Rate Clustering (EEPRC) Technique-based technique for the evaluates the probability ratio in Solar and wind error energy prediction, the error assessment model is proposed, which has the advantage of estimating from real wind farms and statistical Weather Forecast (WF) data and has proven to be a nominal method for improving the predictive accuracy of Multi-term WPG. The primary step of the Energy-Preserve Rate Clustering (EPRC) method is to calculate the uncertainty of real-time data with the predicted value. The computed values are helpful for the increases in Solar WPG production. The proposed wind forecasting system is utilized in the Coastal area-based energy generation. Also, it has been demonstrated that wind speed and WPG with its probability ratio have been evaluated with the EEPRC-based forecasting method, especially for its powerful predictive capability for the complex properties of the controller function. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Solar energy

来源：评论

学校读者我要写书评

暂无评论

Smart Gradational Vehicle Disassembling and Troubleshooting Support Assistant

Smart Gradational Vehicle Disassembling and Troubleshooting ...

引用

Advancements in Computing (ICAC), International Conference on

作者： Suvin Tennakoon Pamuditha Wickramasinha Hasini Ranathunga Chathuranga Ulpathakumbura Dharshana Kasthurirathna Udara Srimath S. Samaratunge Arachchillage Department of Computer Science and Software Engineering Sri Lanka Institute Information Technology Malabe Sri Lanka Department of Information Technology Sri Lanka Institute Information Technology Malabe Sri Lanka

The world of vehicle service and troubleshooting can be daunting for individuals without specialized training. Vehicle manuals are often complex and challenging to comprehend, while relying on experienced mechanics for assistance can be inconvenient and expensive. To address these challenges, this research paper presents the development of an interactive vehicle service assistance system that empowers vehicle owners to independently service and troubleshoot their vehicles. The proposed system encompasses four key components: a knowledgebase construction, write semantic rules (SWRL), real-time object identification using YOLO model, audio feedback and stepwise guidance for customer. The knowledgebase is used for stepwise guidance for disassembling engine through employing marker-less Augmented Reality (AR). The knowledgebase component offers user-friendly access to troubleshooting techniques based on insights from experienced mechanics. By providing stepwise instructions accompanied by AR based visualization, users can effectively learn the process of deconstructing and assembling different components of their automobiles. The proposed system enhances vehicle troubleshooting experiences by enabling owners to acquire the necessary skills to self-troubleshooting without involving external assistance and empower individuals to take control of their own vehicles.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Personalized and Interactive Demented Care and Learning Mate with a Virtual System Using Emotion Recognition

Personalized and Interactive Demented Care and Learning Mate...

引用

Advancements in Computing (ICAC), International Conference on

作者： Nipuna Kaushan Devshan Fernando Chamod Gayashan Sachitha Udayakantha Hansi De Silva Sanduni Perera Department of Information Technology Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Science and Software Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka

This study investigates the development and application of a personalized, interactive virtual system to enhance dementia care and protect people with dementia. A significant challenge in providing care for individuals with dementia is the propensity to wander and become lost, which can lead to anxiety and distress for both the patient and the carers as well as safety concerns. The system combines cutting-edge emotion recognition technology and healthcare IOT technology to effectively identify and provide real-time solutions in response to users' emotional states. This initiative combines dementia care, educational support, and patient security to establish a comprehensive strategy for maintaining well-being and managing the disease in dementia patients. This project has experimentally designed a security system to enhance the safety of dementia patients, a Health Checker system aimed at maintaining their health stability, and a virtual assistant that offers guidance by identifying real-time emotions and providing activities to improve cognitive function and promote relaxation Given a vast amount of patient data, the AI model has been able to identify 98% of patients' illnesses early. security software successfully detected patients with 99% accuracy using GPS technology and machine learning algorithms.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Cell Manipulation Attack Against Onion Services 25

Cell Manipulation Attack Against Onion Services

引用

25th IEEE International Conferences on High Performance Computing and Communications, 9th International Conference on Data science and Systems, 21st IEEE International Conference on Smart City and 9th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Lin, Jianjun Yue, Yinliang Zhang, Yijing Liu, Xiaoyu Yang, XiaoDu Gai, Weilin Sun, Bo Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China Zhongguancun Laboratory Beijing China Institute of Software Chinese Academy of Sciences Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China Beijing China

ISBN: (纸本)9798350330014

In this study, we proposed OREA-OS, a cell manipulation attack devised to compromise Onion Services. Through the manipulation of cells, two collaborating nodes within a circuit exchange information to unveil the anonymity of the targeted Onion Service. We conducted an analysis of existing de-anonymization scenarios and effectively addressed the associated challenges, thereby achieving successful de-anonymization of Onion Services. To assess the efficacy of our attacks, we conducted experiments on both private and public Tor networks. The experimental results validate the effectiveness of our approach, as we accomplished 100% accurate identification of the relationship between domain names and Internet Protocol addresses, with no false positives. Within our simulated private network, the recall rate neared 100 %. On the public Tor network, the de-anonymization rate (98.6 %) exceeded the successful download rate (98.2 %). Furthermore, 99.2 % of success attacks took less than 10 seconds to confirm. © 2023 IEEE.

关键词： Molecular biology

来源：评论

学校读者我要写书评

暂无评论

Facial Skincare Product Suggestion with Product Popularity and Post Recommendation Care

Facial Skincare Product Suggestion with Product Popularity a...

引用

2023 4th International Informatics and software engineering Conference (IISEC)

作者： H. M. W. T. C. B. Samarakoon A. U Ovitigala G. A. T. T. Wijesinghe K. M. L. P. Weerasinghe G. K. B. V. Karunathilake Ishara Weerathunga Department of Computer Science and Software Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Sri Lanka Institute of Information Technology Malabe Sri Lanka

Skin health significantly affects a person's overall wellbeing, which includes both physical and emotional aspects. The objective of this study is to develop an integrated system for recommending skincare products that integrates image processing, machine learning, sentiment analysis, and user feedback analysis to deliver individualized skincare advice and boost user satisfaction. Utilizing deep learning algorithms and face cues, the system uses user image analysis to detect important skin features, skin type, acne severity, and dark spots with extraordinary accuracy. Using sentiment analysis and clustering, the program identifies popular skincare products and tailors’ recommendations to user preferences. Recommendations are further personalized by collaborative filtering. By using image analysis to identify allergies and other negative effects, user safety is increased. The technique prioritizes data safety and includes model training, sentiment analysis, image processing, and user input analysis. Initial findings demonstrate the excellent accuracy of skin issue detection and severity prediction. By allowing users from a variety of user demographics to make informed skincare decisions, this complete framework has the potential to change the skincare industry.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Accurate Stress Detection for Developers: Leveraging Low-Cost IoT Devices (ESP32 and MAX30102) to Analyze Heart Rate Variability via an External Mouse

Accurate Stress Detection for Developers: Leveraging Low-Cos...

引用

Advancements in Computing (ICAC), International Conference on

作者： Amantha Jayathilake Janudi Ranasinghe Dulshan Perera Shehan Bartholomeusz Samadhi Rathnayake Devanshi Ganegoda Department of Computer Science and Software Engineering Sri Lanka Institute of Information Technology Colombo Sri Lanka Department of Information Technology Sri Lanka Institute of Information Technology Colombo Sri Lanka

In today's fast-paced work environment, stress levels have become a critical concern. This research introduces an innovative approach to address this issue by utilizing readily available, cost-effective components - the ESP32 microcontroller and the MAX30102 heart rate sensor, seamlessly integrated into an external mouse. This non-intrusive system enables real-time stress assessment for developers during their tasks. By analyzing heart rate variability data, a practical and effective solution is offered. The collected data is securely transmitted for analysis, potentially revolutionizing developer well-being and productivity. This study pioneers a unique and practical stress detection solution finely tuned to the software development milieu.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Enhancing Android malware detection via knowledge distillation on homogenized function call graphs

引用

Knowledge-Based Systems 2025年 323卷

作者： Wang, Zhendong Zhang, Kaiyi Yang, Shuxin He, Daojing Chan, Sammy School of Information Engineering Jiangxi University of Science and Technology Jiangxi Ganzhou341000 China Software Engineering Institute Nanchang University Jiangxi Nanchang330047 China School of Computer Science and Technology Harbin Institute of Technology Guangdong Shenzhen518055 China Department of Electrical Engineering City University of Hong Kong Hong Kong

Graph neural network (GNN)-based Android malware detection has demonstrated significant potential for accuracy enhancement. However, existing function call graph (FCG) classification methods face two critical limitations: (1) inherent incompatibility between graph heterogeneity and model homogeneity assumptions, and (2) performance degradation in conventional GNNs when processing large-scale FCGs. This paper introduces a novel Android malware detection method (SIGDroid) that addresses these challenges through two key contributions. First, we propose a heterogeneous-to-homogeneous graph transformation technique that simplifies the structural complexity of the graph by focusing on internal function nodes directly related to malicious behaviors while preserving critical malware-related features, including API calls, permissions, and semantic information. Second, we design a Student-Centered Knowledge Distillation framework on Graphs (SCKDG). Diverging from teacher-centric paradigms, SCKDG prioritizes the student model's learning requirements through a multi-stage adaptive distillation mechanism. The framework dynamically adjusts knowledge propagation strategies based on the student model's evolving capabilities, implementing a progressive learning process analogous to personalized educational methodologies. Extensive experiments were conducted on two large-scale datasets, simulating real-world scenarios with nearly 144k samples, and the results were compared against those of eight baseline methods. Compared to existing malware detection methods, our approach demonstrates superior performance over other methods that rely on heterogeneous function call graphs. Compared to standard GNN models, our SCKDG method achieves a maximum F1-score improvement of 2.91%. © 2025 Elsevier B.V.

关键词： Android malware

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：