检索结果-内蒙古大学图书馆

IEEE International Conference on Electro-Information Technology

作者： Ahlam Al Mohammad Daniel Marku John Reedy Stephen Reedy Mina Maleki Shadi Banitaan Dept. of Electrical & Computer Engineering & Computer Science University of Detroit Mercy Detroit MI United States

ISBN: (数字)9798350330649

ISBN: (纸本)9798350330656

Location-based services in commercial and industrial settings enhance power efficiency and security by providing real-time visibility of people within designated areas. Indoor facilities, in particular, benefit from accurate indoor localization to optimize resources and ensure a safe environment. This study presents an approach to localizing wireless access points (APs) within indoor environments using a handheld smartphone. The method leverages received signal strength indicator (RSSI) scans from APs via fingerprints and employs a customized localization algorithm. Three localization algorithms—filtration, non-linear, and linear trilateration—are explored to determine the most effective means of AP estimation within commercial buildings. The filtration process includes discarding the least reliable RSSI scans, identifying the predominant floor number, and enhancing accuracy through a weighted average computation using RSSI values. Meanwhile, the trilateral linear and non-linear approaches utilize a multilateral localization algorithm to estimate the location of an AP. Results indicate that the filtration approach yields the closest estimates to the AP’s real location, with an average of 2.4 meters or 8 feet away. In contrast, non-linear trilateration is more consistently close to the AP but with a noticeably further average prediction margin, while linear trilateration exhibits skewed results due to extreme outliers. Filtration is thus the preferable method as long as sufficient data is collected for accurate estimation. In conclusion, given the available data, the filtration approach emerges as the most suitable method for AP estimation in commercial buildings, producing estimates that are heavily weighted towards the closest possible AP location. However, ensuring adequate data collection for accurate localization results is essential.

关键词： Location awareness Meters Accuracy Filtration Buildings Estimation Fingerprint recognition

来源：评论

学校读者我要写书评

暂无评论

Exploration and Evaluation of Machine Learning Methods for Detecting Oil Spills in Open Seas

Exploration and Evaluation of Machine Learning Methods for D...

引用

2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Sibai, Fadi N. Sibai, Ahmad El-Moursy, Ali GUST Engineering & Applied Innovation Research Center Gulf Univ. for Science and Tech. West Mishref Hawalli Kuwait Univ. of South Florida Computer Science & Engg. Dept. TampaFL United States Univ. of Sharjah Comp. Engg. Dept. Sharjah United Arab Emirates

ISBN: (纸本)9798350369106

Detecting oil spills in open seas is important for the early containment of the pollution diffusion and avoidance of further ecological catastrophes. Herein, we explore and assess the application of several machine learning (ML) methods and image processing techniques for the detection of oil spills in images of open seas captured at the elevation of planes, helicopters, or drones. The image dataset used contains 24 clean sea images and 24 dirty sea images with oil slicks. The machine learning methods experimented with include neural networks, SVM, random forest, decision tree, naïve Bayes, AdaBoost, and logistic regression. We also evaluated these ML methods with and without the application of Sobel Feldman edge detection and Vintage filtering image processing techniques. Results indicate the superiority of the in and neural networks methods over the other explored ML methods, achieving perfect and near-perfect classification, respectively. © 2024 IEEE.

关键词： Oil spills

来源：评论

学校读者我要写书评

暂无评论

Blockchain-based certificate authentication system with enabling correction

arXiv

引用

arXiv 2023年

作者： Rahman, Md. Mijanur Tonmoy, Md Tanzinul Kabir Shihab, Saifur Rahman Farhana, Riya Dept. of Computer Science and Engineering Southeast University Bangladesh

Blockchain has proven to be an emerging technology in the digital world, changing the way everyone thinks about data security and bringing efficiency to several industries. It has already been applied to a wide range of applications, from financial services and supply chain management to voting systems and identity verification. An organization must verify its candidates before selecting them. Choosing an unqualified candidate can ruin an organization’s reputation. In this digital era, many key fraudulent schemes are rampant in many companies and one of them is certificate fraud. It is possible to validate a candidate’s qualifications using traditional methods, but there are drawbacks such as security issues and time consumption. In this paper, a blockchain-based academic certificate authentication system will be used to ensure authenticity and make the assertion of the decentralized system secure. However, the system will generate, authenticate and make corrections on academic certificates. Ultimately, some blockchain-based authentication systems already exist, they can’t correct any errors that occur during generation. The proposed system will help in many ways, such as providing a user-friendly university admission, and smooth job hiring process, etc. In conclusion, our proposed system can permanently eradicate certificate forgeries and create and promote trust in society. © 2023, CC BY.

关键词： Authentication

来源：评论

学校读者我要写书评

暂无评论

Reviewlogy: An Interface for Analyzing Sentiments

Reviewlogy: An Interface for Analyzing Sentiments

引用

Applied Intelligence and Computing (AIC), IEEE World Conference on

作者： Radhey Shyam Shilpi Khanna Kavya Srivastava Ajay Kumar Srivastava Ishika Chaudhary Dept. of Computer Science & Engineering BBD University Lucknow India Dept. of Information Technology SRMCEM Lucknow India

ISBN: (数字)9798350384598

ISBN: (纸本)9798350384604

This paper investigates the impact of early reviews on product sales by analyzing the traits of initial reviewers on major e-commerce platforms. It segments product life-cycles into three phases: early, majority, and laggards, focusing on early reviewers who post reviews during the initial stages. The paper introduces an innovative interface for sentiment analysis to identify and predict early reviewers. Quantitative analysis reveals that early reviewers often provide more insightful comments and give higher overall ratings. Their ratings and helpfulness scores significantly affect product popularity. The methodology, tested on extensive datasets from Amazon and Yelp, extracts crucial attributes of early reviewers, including purchasing patterns and social impact. The interface employs a hybrid machine learning approach combining Naive Bayes, margin-based embedding ranking models (MERM), and support vector machines (SVMs) to predict potential early reviewers accurately. This approach balances probabilistic reasoning with robust classification, ensuring comprehensive forecasting. Evaluation metrics such as precision and accuracy demonstrate the effectiveness of the models over baseline methods. Furthermore, the study enhances the understanding of how early reviews influence consumer behavior and product success in e-commerce. The interface aids in refining product marketing strategies by enabling precise targeting of early reviewers, accelerating product adoption, amplifying sales, and optimizing marketing tactics in the competitive e-commerce landscape.

关键词： Support vector machines Measurement Sentiment analysis Reviews Statistical analysis Refining Machine learning Predictive models Probabilistic logic Electronic commerce

来源：评论

学校读者我要写书评

暂无评论

Using Machine Learning and Google Earth Engine to Understand Land Use and Land Cover Classifications and NO2 Levels in California

Using Machine Learning and Google Earth Engine to Understand...

引用

IEEE International Conference on Electro-Information Technology

作者： Benyamain Yacoob Ethan Scheys Eyiara Oladipo Andre Price Shadi Banitaan Dept. of Electrical & Computer Engineering & Computer Science University of Detroit Mercy Detroit MI United States

ISBN: (数字)9798350330649

ISBN: (纸本)9798350330656

Anthropogenic activities release pollutants into the air, which can negatively affect human health and the environment. One such pollutant is nitrogen dioxide (NO 2 ), which can contribute to smog formation, decreased crop growth and yield, and respiratory damage. This study aimed to find a relationship between land use/land cover (LULC) classifications and NO 2 levels in the air. We used Google Earth Engine (GEE) to collect LULC and air quality data using the Google Dynamic World and the Sentinel-5P NRTI NO 2 datasets. We focused on Pasadena, California, as it provided a good demonstration of an urban area surrounded by greenery, allowing for an adequate analysis of both forms of landscape and their impact on air quality. Random forest (RF) and decision tree (DT) classifiers were used on the provided datasets, with the estimated probability of complete coverage for each LULC type being the input features and the NO 2 density being the output label, measured in mol/m 2 . Our output labels were then discretized, classifying the categories into high and low NO 2 . The machine learning classifier found a correlative relationship between LULC and NO 2 levels, as signified by our modeled accuracy outputting a value of 85%, with an average f1 score of 86%. We performed 10-fold cross-validation to enhance the reliability of model evaluation. The results from this study suggest that machine learning models can be used to predict the changes in air quality based on changes in LULC from anthropogenic activities. With future studies confirming this relationship, inner-city green spaces may benefit mental and physical well-being.

关键词： Earth Atmospheric modeling Green products Urban areas Predictive models Air quality Internet

来源：评论

学校读者我要写书评

暂无评论

Harmonizing open banking in the European Union: an analysis of PSD2 compliance and interrelation with cybersecurity frameworks and standards

引用

International Cybersecurity Law Review 2024年第1期5卷 79-120页

作者： Gounari, Marianna Stergiopoulos, George Pipyros, Kosmas Gritzalis, Dimitris Dept. of Information & Communication Systems Engineering University of the Aegean Samos Greece Dept. of Computer Science Philips University Nicosia Cyprus Dept. of Informatics Athens University of Economics & Business Athens Greece

This paper focuses on the security protocols enacted in banking transactions across the European Economic Area (EEA), as stipulated by the Second or Revised Payment Service Directive (commonly referred to as ‘PSD2’ or simply ‘the Directive’). The study aims to comprehensively analyse the implementation and efficacy of these security measures within the specified jurisdiction. The Directive incorporates fundamental rights and obligations that all stakeholders are compelled to adhere to and delineates specific security measures and standards that both traditional banking institutions and third-party providers (TPP) are mandated to implement. In particular, one of the cardinal mandates for banking and financial institutions under PSD2 is the obligation to facilitate third-party access to customer data via open application programming interfaces (API). While this open banking paradigm and the consequent proliferation of data sharing unquestionably bring about various advantages, such as enhanced consumer choice and market competition, they concurrently expose the financial ecosystem to a slew of potential security vulnerabilities and privacy risks. Upon conducting a comprehensive review of the security requirements and measures stipulated under PSD2 and a comparative analysis with essential cybersecurity frameworks and standards (NIS2, Cybersecurity Act, GDPR, ISO 27001:22 and PCI DSS), we have ascertained a discernible lack of harmonisation and clarity concerning the technical security specifications for its effective implementation. This lacuna substantiates the challenges banks face in fully grasping the extensive spectrum of compliance obligations mandated by PSD2. The aim of this research is to offer a valuable contribution to both the comprehension and the pragmatic deployment of security standards in the context of banking transactions, as regulated by the PSD2. The paper serves as a valuable resource for traditional banking institut

关键词：

来源：评论

学校读者我要写书评

暂无评论

Feasibility of Wide Area Network Traffic Distribution in Cloud Computing Enabled Wireless Networks

Feasibility of Wide Area Network Traffic Distribution in Clo...

引用

2024 International Conference on E-Mobility, Power Control and Smart Systems, ICEMPS 2024

作者： Mimani, Sushant Pillai, Sanjaikanth E. Vadakkethil Somanathan Jindal, Mayank Jiwani, Nasmin Kiruthiga, T. GoDaddy SnohomishWA United States School of Electrical Engineering and Computer Science University of North Dakota Grand Forks United States San Jose CA United States University of The Cumberlands Dept. of Information Technology WilliamsburgKY United States Vetri Vinayaha College of Engineering and Technology Dept. of Ece Trichy India

ISBN: (纸本)9798350394399

Cloud computing enabled Wi-Fi networks provide an outstanding opportunity for corporations to distribute extensive area community (WAN) site visitors and advantage from reduced latency because of the proliferation of hyper connectivity. The feasibility of implementing a Wide Area Network (WAN) traffic distribution system in cloud computing enabled wireless networks was studied. The study aimed to determine the practicality and effectiveness of this approach in improving network performance. For the experiment, a sample network topology was designed to simulate real-world scenarios and subjected to diverse traffic loads. The results showed that the WAN traffic distribution system was indeed feasible and could effectively distribute and balance network traffic in cloud computing enabled wireless networks. Furthermore, key metrics such as network latency, packet loss, and throughput were significantly improved compared to traditional networks without the WAN distribution system. Further research and development in this area could potentially lead to improved network efficiency and enhanced user experience in the rapidly growing field of cloud computing. Those consequences reveal the feasibility of deploying WAN site visitors distribution in cloud computing-enabled wireless networks, and serves as a starting point for further study aiming to improve the performance of such networks. © 2024 IEEE.

关键词： Wide area networks

来源：评论

学校读者我要写书评

暂无评论

Hybrid Vision Transformer Model for Accurate Prostate Cancer Classification in MRI Images

Hybrid Vision Transformer Model for Accurate Prostate Cancer...

引用

International Conference on Electrical, computer and Communication engineering (ECCE)

作者： Jesika Debnath Arafath Bin Mohiuddin Al Shahriar Uddin Khondakar Pranta Anamul Sakib Amira Hossain Md. Moniruzzaman Shanto Shamim Forhad Md. Redwan Ahmed Rezaul Haque Shafiur Rahman Dept. of Computer Science Westcliff University Irvine CA USA Department of Collage of Engineering and Technology Westcliff University CA USA Dept. of Computer Science Wright State University Dayton USA Department of Business Administration International American University CA USA Dept. of Computer Science and Engineering East West University Dhaka Bangladesh Dept. of Electrical and Electronics Engineering American International University Bangladesh Dept. of Software Engineering Daffodil International University Dhaka Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

Prostate cancer is a widespread disease in men worldwide, posing challenges in early detection due to its diverse nature and the limitations of current diagnostic techniques. In this study, we have developed a new method that combines CNNs with Vision Transformers (ViTs) to improve the classification of prostate cancer using MRI images. To address data imbalance and enhance model robustness, we used dual synthetic oversampling techniques and data augmentation methods. Our preprocessing pipeline reduced noise, preserved edges, and improved local contrast without amplifying noise. For feature extraction, we utilized the GrayLevel Co-occurrence Matrix (GLCM) and shape-based features to represent complex MRI data better. Among the evaluated architectures, ConvNeXt showed the best performance. Using SMOTE, it achieved an F1-score of 97.21% and a MCC of 95.32%. With ADASYN, performance improved further, reaching an F1-score of 98.82% and an MCC of 97.86%. Additionally, we created a web-based application for realtime analysis of prostate MRI scans, which can aid in clinical decision-making. These results demonstrate the potential of our approach to improve the accuracy of prostate cancer diagnosis and provide an interpretable model for clinical use.

关键词： computer vision Accuracy Magnetic resonance imaging Noise Pipelines Transformers Feature extraction Robustness Prostate cancer Resilience

来源：评论

学校读者我要写书评

暂无评论

Smart Mushroom Cultivation: Enhancing Growth Conditions through Sensor-Based Monitoring

Smart Mushroom Cultivation: Enhancing Growth Conditions thro...

引用

Advances in Computation, Communication and Information Technology (ICAICCIT), International Conference on

作者： Ishaan Rana Ankit Gupta Rakshit Mittal Harshita Chaudhary Shobha Tyagi Pronika Chawla Dept. of Computer Science and Engineering MRIIRS Faridabad India

Smart mushroom cultivation using remote sensing involves the integration of advanced technology to optimize the growth and productivity of mushrooms. Remote sensing techniques using arduino, sensors and cloud services are employed to monitor and manage various farming and growth related parameters in mushroom farms. Using the remote sensing of mushroom fields provides a macroscopic view of environmental conditions, helping farmers identify suitable locations for mushroom cultivation based on factors like temperature, humidity, and vegetation cover. Ground-based sensors are strategically placed within the cultivation area to measure crucial variables like temperature and humidity levels. These sensors transmit data to a central control system, allowing farmers to maintain optimal conditions for mushroom growth. Automated climate control systems can adjust parameters in response to real-time data, ensuring consistent and ideal growing conditions. This enables timely intervention, reducing crop loss and the need for chemical treatments. Furthermore, remote sensing can improve resource management. Precise water and nutrient monitoring based on sensor data can lead to more efficient resource utilization, reducing waste and operating costs. In summary, smart mushroom cultivation using remote sensing technology optimizes environmental monitoring, and resource usage. By harnessing the power of remote sensing, mushroom farmers can increase yields, reduce environmental impact, and enhance the overall sustainability and profitability of their operations.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Enhancing Multi-label text classification using adaptive promptify concepts

Enhancing Multi-label text classification using adaptive pro...

引用

International Conference on Computing and Networking Technology (ICCNT)

作者： Veerababu Reddy Usha Rani Uppukonda N. Veeranjaneyulu Dept. of Computer Science & Engineering Vignan’s Foundation for Science Technology & Research Guntur India Dept. of Computer Science & Engineering Vignan’s Lara Institute of Technology & Science College Guntur India Dept. of Information Technology Vignan’s Foundation for Science Technology & Research Guntur India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

In present days, Multi Label Text Classification (MLTC) has become an important research area in Natural Language Processing (NLP). Existing models of MLTC have been facing domain specificity and fine-tuning challenges. Hence a model is developed to overcome the above said challenges by introducing Prompt engineering, GPT FineTuning methods and Pipeline algorithms. The experimental results are obtained based on the present Generative pre trained data produces labels for various text documents and files with an exceptional accuracy of 85%. The outcomes of the experiments reveal notable enhancements over the baseline models.

关键词： Surveys Accuracy Social networking (online) Text categorization Pipelines Medical services Natural language processing Prompt engineering Optimization Sorting

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：