检索结果-内蒙古大学图书馆

Towards smart technologies with integration of the internet of things, cloud computing, and fog computing

International Journal of Networking and Virtual Organisations 2023年第1期29卷 73-124页

作者： Ahlawat, Chanchal Krishnamurthi, Rajalakshmi Department of Computer Science and Engineering Jaypee Institute of Information Technology Noida201309 India

In the recent era of technology, the internet of things (IoT) plays a tremendous role in enhancing the quality of human life through smart devices and sensing the real-world environment. IoT aims to interconnect anything from anywhere via the internet. The existing literature lacks in providing deeper research insight toward a broader perspective of integrating IoT, cloud computing (CC), and fog computing (FC). Hence, this paper aims to provide a comprehensive review of integrating these main emerging technologies and four major objectives are addressed. The first objective identifies the primary characteristics of IoT to solve real-life problems. The second objective addresses the issues that necessitate the integration of IoT with other emerging technologies. The third objective involves how the integration of IoT with CC elevates the scope of providing a solution to real-life problems. The final objective addresses the limitations of the integration of IoT with CC and how FC overcomes these limitations. © 2023 Inderscience Enterprises Ltd.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Based Signal Detection for Quadrature Spatial Modulation System

引用

China Communications 2024年第10期21卷 78-85页

作者： Shu Dingyun Peng Yuyang Yue Ming Fawaz AL-Hazemi Mohammad Meraj Mirza School of Computer Science and Engineering Macao University of Science and TechnologyMacaoChina Department of Computer and Network Engineering University of JeddahSaudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia

With the development of communication systems, modulation methods are becoming more and more diverse. Among them, quadrature spatial modulation(QSM) is considered as one method with less capacity and high efficiency. In QSM, the traditional signal detection methods sometimes are unable to meet the actual requirement of low complexity of the system. Therefore, this paper proposes a signal detection scheme for QSM systems using deep learning to solve the complexity problem. Results from the simulations show that the bit error rate performance of the proposed deep learning-based detector is better than that of the zero-forcing(ZF) and minimum mean square error(MMSE) detectors, and similar to the maximum likelihood(ML) detector. Moreover, the proposed method requires less processing time than ZF, MMSE,and ML.

关键词： bit error rate complexity deep learning quadrature spatial modulation

来源：评论

学校读者我要写书评

暂无评论

Harnessing Social Media Data for Text Classification During Emergency 2024

Harnessing Social Media Data for Text Classification During ...

引用

16th International Conference on Contemporary Computing, IC3 2024

作者： Dixit, Ankita Chawla, Indu Department of Computer Science & Engineering and Information Technology Jaypee Institute of Information Technology Noida India

ISBN: (纸本)9798400709722

Social media platforms offer a plethora of valuable resources in times of disaster. Social media platforms like Twitter allow the sharing of information by individuals in the time of crisis. In this study, highlights difficulty in differentiating between situation related tweets and are intend to investigate the belongingness of tweets that are related to the disaster or not related to the disaster. This work proposes an exploration of n-gram-based feature extraction in the form of unigram, bigram, and trigram. Further combinations of unigram, bigram and trigram have been taken with cut-off value 50%. To intensify performance, the two-step ensemble stacking method is implemented to categorize tweets by enhancing the diversity among the base learners and utilizing the meta-learner to merge the predictions made by base learners. To verify the approach, experimentation done with ensemble method and then compared with linear and non-linear machine learning algorithms. The obtained result shows stacking ensemble method with decision tree as meta learner gives the best results. The findings of the study revealed that our proposed method demonstrates a robust solution to help identify disaster related tweets during a disaster and empower individuals, groups, and organizations to improve communication during emergencies. © 2024 Copyright held by the owner/author(s).

关键词： Tweets

来源：评论

学校读者我要写书评

暂无评论

Exploring the Performance of Diffusion Models in Weighted Social Networks 2

Exploring the Performance of Diffusion Models in Weighted So...

引用

2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Singhal, Megh Saxena, Bhawna Jaypee Institute of Information Technology Department of Computer Science & Engineering and Information Technology Noida India

ISBN: (纸本)9798350371055

In the present time, social networks have become a quintessential part of people's lives, by transforming how people connect and communicate. Social networks have become an important medium for information diffusion and social interactions. The rate of diffusion often depends upon network topology, influencing power of the initial adopters and the underlying node activation criteria. Most real-world social networks are weighted in nature, with edge weights representing the tie strength between the two connected nodes. In our research, we explore and analyze the performance of popular diffusion models in weighted social networks. The performance of 4 prevalent diffusion models, namely - Independent Cascade, Weighted Cascade, Trivalency and Linear Threshold, is compared with regards to the attained spread of information. The study was performed on 2 real-world weighted social networks. © 2024 IEEE.

关键词： Independent Cascade Influence Maximization information Diffusion Linear Threshold Weighted Social Networks

来源：评论

学校读者我要写书评

暂无评论

Gene Variant Analysis for the Detection of Hemophilia: A Literature Review

引用

Recent Patents on engineering 2024年第9期18卷 48-62页

作者： Sumathi, N. Anitha Kumari, K. Department of Computer Science and Engineering Dr. Mahalingam College of Engineering and Technology Tamil Nadu Pollachi India Department of Information Technology PSG College of Technology Tamil Nadu Coimbatore641004 India

Background: Proteins act as clotting factors to stop bleeding at the lesion site. This implies that people with hemophilia tend to bleed longer after an injury and are more prone to internal bleeding. Depending on the type of hemophilia, individuals with hemophilia will have lesser amounts of factor VIII or factor IX than people without it. Objective: By analyzing the gene variant of hemophilia affected patient we can predict the severity of disease at earlier stage which helps to avoid further complications. Methods: Predicting hemophilia can be achieved through potential technologies like machine learning. Using these technologies, one can detect and predict the severity of hemophilia, such as mild, moderate, or severe. Results: By comparing the methods used in protein structure analysis, the advantages and limitations of methods used in protein structure analysis are discussed. Conclusion: The best practices in predicting hemophilia are highlighted in this patent study and particularly aim at the basic understanding of applying the potential technologies in the prediction of hemophilia and its severity. This study represents recent research on hemophilia and the use of different machine learning techniques (MLT) in this area. © 2024 Bentham Science Publishers.

关键词： Proteins

来源：评论

学校读者我要写书评

暂无评论

Click Fraud Detection Using Ensemble Classifier 1

引用

3rd International Conference on Artificial-Business Analytics, Quantum and Machine Learning: Trends, Perspectives, and Prospects, Com-IT-Con 2023

作者： Purwar, Archana Jain, Art Chawla, Indu Gupta, Ishita Raj, Mayank Jain, Divansh Department of Computer Science and Engineering and Information Technology Jaypee Institute of Information Technology Noida India

ISBN: (数字)9789819748600

ISBN: (纸本)9789819748594

Online advertising fraud is an emerging issue and has drawn researchers’ mind recently because it now poses a significant danger to an online advertising sector. A content publisher signs an agreement to place advertisements on various websites in exchange for commissions on the basis of the amount of traffic these advertisements generate. It may sometimes motivate fraudulent publishers to produce unauthorized clicks on their websites in order to maximize traffic to the advertisements, a practice known as click fraud. Although click fraud is identified as a huge issue, there are not many algorithms that have been able to effectively solve this problem. Our aim in this paper is to overcome the problem of click fraud and come up with an explicit model for the click fraud detection. In this paper, a model is proposed using recursive feature elimination (RFE) and ensemble classifier with Hellinger distance-based decision tree (HDDT). The proposed model is evaluated over the dataset hosted by a Chinese company TalkingData available freely from Kaggle and has resulted in an accuracy of 99.72% as compared to the traditional decision tree. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Marketing

来源：评论

学校读者我要写书评

暂无评论

Student Placement Prediction Using Machine Learning Algorithms 2nd

Student Placement Prediction Using Machine Learning Algorith...

引用

2nd International Conference on Emerging Trends in engineering and technology, EGTET 2022

作者： Sajwan, Samarth Bhardwaj, Rudraksh Mishra, Revaan Jaiswal, Shruti Department of Computer Science and Engineering and Information Technology Jaypee Institute of Information Technology Noida India

ISBN: (纸本)9789819943616

One of the most perplexing issues confronting higher education institutions today is how to increase student placement performance. Placement estimation becomes more complex as the number of educational institutions increases. Educational organizations explore more efficient technologies to assist them in improving their decision-making practices, as well as in developing creative methods. Providing new insight into instructional processes is a critical component in resolving quality issues. Machine learning methods are used to extract information from historical data contained in the libraries of educational organizations. Our model will generate a recommendation system that forecasts the placement level of a student. This model assists an organization’s selection cell in identifying prospective students, assessing their technical and interpersonal abilities, and assisting them in developing them. Students in their pre-final and final years of B. Tech programs may also use this work to determine their individual placement status and probability of achieving it. This enables them to exert additional effort in order to get placements in organizations with higher hierarchies. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

PQTD-TM: Integrating information Retrieval with Machine Learning for effective Placement Topic Discovery 2024

PQTD-TM: Integrating Information Retrieval with Machine Lear...

引用

16th International Conference on Contemporary Computing, IC3 2024

作者： Sardana, Neetu Kumar, Prabudh Goyal, Kritank Rishi Jain, Nehal Arora, Anuja Varshney, Deepika Department of Computer Science & Engineering and Information Technology Jaypee Institute of Information Technology Noida India

ISBN: (纸本)9798400709722

Technical interviews, particularly coding rounds, are pivotal in shaping career trajectories, especially for roles in top-tier companies like Amazon, Google, and Microsoft. Understanding the patterns and nuances of coding problems and their associated tags is essential for effective interview preparation. To aid candidates in excelling in these assessments, we analyzed coding problems encountered in such interviews. We compile a comprehensive dataset of coding problems and their associated tags, sourced from real technical interviews, ensuring reliability and relevance. We propose a topic prediction approach for placement related questions, PQTD-TM (Placement question topic discovery using TF IDF and Machine Learning). The proposed technique integrates information retrieval technique (TF-IDF) with six machine learning classifiers for prediction. We evaluated the predictive performance of various machine learning models, including Logistic Regression, Decision Trees, Naive Bayes, KNN, One-vs-Rest Classifier, and Random Forest. Random forest attained the best prediction accuracy of 93%. © 2024 Copyright held by the owner/author(s).

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Early Diagnosis of Alzheimer’s Disease with Transfer Learning Techniques Via ResNet50 and FSBi-LSTM

Informatica (Slovenia)

引用

Informatica (Slovenia) 2025年第11期49卷 149-164页

作者： Khaleel, Z.S. Lakizadeh, Amir Computer Engineering and Information Technology Department University of Qom Qom Iran Department of mathematic Open Educational College Basra Study Center Iraq

Alzheimer's Disease (AD) is a neurological disorder marked by cognitive deterioration and neurological impairment that affects cognition, memory, and behavioral patterns. Alzheimer's is an incurable disease that predominantly impacts individuals over the age of 40. A patient's MRI (Magnetic Resonance Imaging) scan and cognitive assessment are manually analyzed to diagnose Alzheimer's disease. Recently, Artificial Intelligence (AI), particularly through Deep Learning, has pioneered innovative techniques for automated medical image identification. We devised a deep learning methodology for Alzheimer's disease identification utilizing Magnetic Resonance Imaging (MRI) data. The suggested method, termed Res+FSBILSTM, employs ResNet50 as a pre-trained model for feature extraction from MRIs, thereafter identifying Alzheimer's disease through a Fully-Stack Bidirectional Long-Short Term Memory deep learning model. The experimental results demonstrate that the suggested method surpasses state-of-the-art techniques across all evaluation metrics, rendering it a viable tool for medical professionals in identifying Alzheimer's disease using brain radiological images. Ultimately, we achieved results with an accuracy of 99.6%, an F1-score of 97.7%, an area under the curve of 99%, a recall of 97.3%, and a precision of 99.6%. © 2025 Slovene Society Informatika. All rights reserved.

关键词： Magnetic resonance imaging

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Driven Edge-Enabled Serverless Architectures for Animal Emotion Detection

Informatica (Slovenia)

引用

Informatica (Slovenia) 2025年第7期49卷 33-48页

作者： Benedict, Shajulin Subair, Rubiya Department of Computer Science and Engineering Indian Institute of Information Technology Kottayam Kerala India Technical University Munich Garching Germany

Animal emotion detection, including elephant emotions, is highly possible, but what the traditional emotion detection approaches highlight is their blatant ignorance of adopting edge-enabled intelligence and serverless-based solutions, both of which are affordable. Treating the emotions of animals increases their productivity, especially among trained elephants when subjected to carrying logs or undertaking gargantuan tasks. However, existing infrastructures are inefficient in handling long-running animal emotion detection-related tasks. This article proposes a deep learning-driven edge-enabled serverless architecture after evaluating several existing animal emotion detection techniques. Additionally, we perform an exploratory study on the cost impact of incorporating serverless-enabled approaches to animal emotion detection architectures. We observed that the proposed edge-enabled serverless architectures saved over 13,000 dollars annually compared to traditional animal emotion detection approaches. In addition, the article provided a few research directions to develop novel edge-enabled serverless architectures that boost socio-economic situations while avoiding human-animal conflicts. © 2025 Slovene Society Informatika. All rights reserved.

关键词： Invertebrates

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：