检索结果-内蒙古大学图书馆

25th International Arab Conference on information technology, ACIT 2024

作者： Hassan, Tahir Mansour, Khalid Waseemullah, Waseemullah Memon, Muhammad Qasim Ned University of Engineering and Technology Department of Computer Science & Information Technology Karachi Pakistan Arab Open University Faculty of Computer Studies Bahrain Sindh Bhitshah Pakistan

ISBN: (纸本)9798331540012

Climate change is considered a global disaster that has wreaked havoc worldwide. Climate change conditions are primarily driven due to emission of carbon dioxide and other greenhouse gases. Around the globe, several countries are facing serious challenges related to global warming and climate change. The adverse effects of global warming and climate change are recently observed in the form heat waves, floods, extreme rainfall events and drought conditions. The escalating CO2 emission level causes threats of food security and water scarcity. To overcome this, timely and accurate CO2 emissions forecasting is essential for developing effective mitigation strategies in such a manner that CO2 emission impacts can be reduced. The aim of this study is to forecast the total CO2 emissions of upcoming years using various statistical, machine learning models such as ARIMA (Auto-Regressive Integrated Moving Average), SARIMA (Seasonal ARIMA), Linear Regression, and Decision tree regressor. We had forecasted CO2 emission on the basis of influencing factors, which highly contributes in CO2 emission. The performance of the models is validated using multiple evaluation metrics such as MAE, MSE RMSE,MAPE and R2 square. The results show that CO2 emission is highly affected by fossil fuel consumption. In particular, Linear regression performs better among all applied models, with R2 value 0.93 and MAE, RMSE and MAPE values 5.52, 6.47 and 0.03, respectively. Our research delineates the results and insights that will assist concerned authorities, policymakers and environmental agencies. The present study also aim to inform authorities, helping them to better understand the future of CO2 emission trajectories and make timely efforts and interventions to tackle the climate change and global warming challenges. © 2024 IEEE.

关键词： Low emission

来源：评论

学校读者我要写书评

暂无评论

Ensemble Learning for Breast Cancer Image Classification Using Pre-trained CNNs and Random Oversampling Method 5

Ensemble Learning for Breast Cancer Image Classification Usi...

引用

5th International Conference on Advanced information Technologies, ICAIT 2024

作者： Thuzar, Win Myat Moe Htay, Moe Uinversity of Computer Studies Mandalay Department of Information Technology Supporting and Maintenance Mandalay Myanmar Uinversity of Computer Studies Mandalay Faculty of Computer Science Mandalay Myanmar

ISBN: (纸本)9798331510046

The classification of breast cancer images presents significant challenges, especially when dealing with imbalanced datasets that underrepresent minority classes. This study tackles the issue by implementing ensemble learning techniques with pre-trained convolutional neural networks (CNNs) such as ResNet50, GoogleNet, and EfficientNet. The random oversampling method was employed to address the imbalance, which effectively increases the representation of minority classes within the dataset. This study performs detailed data analysis after this adjustment to improve the model's ability to identify these minority classes. By combining the predictions of the three models into an ensemble, the approach aims to improve both the accuracy and robustness of the classification process. The ensemble method works much better at finding minority classes, as shown by the results of experiments. This proves that it can handle uneven datasets when classifying breast cancer images. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Measurement of ChatGPT Performance in Mapping Natural Language Speficaction into an Entity Relationship Diagram 11

Measurement of ChatGPT Performance in Mapping Natural Langua...

引用

11th IEEE International Conference on systems and Control, ICSC 2023

作者： Omar, Mussa A. University of Ajdabiya Faculty of Information System Computer Science Department Libya

ISBN: (纸本)9798350304886

This paper explores the entity relationship diagram, a popular conceptual model used to depict entities, attributes, and relationships graphically. To help with this, we use ChatGPT, a sophisticated language model based on the GPT architecture, which can translate natural language text into an entity relationship diagram. The paper details the process of evaluating how well ChatGPT can perform compared to other state-of-the-art approaches for entity and relationship extraction. Our experimental findings demonstrate the strong ability of ChatGPT to translate natural language text into entity relationship diagrams, which has potential applications for knowledge graph building, data integration, and database schema design. Moreover, it can aid in automating the extraction and organization of information from unstructured text data, thereby simplifying the study of complex systems. © 2023 IEEE.

关键词： Knowledge graph

来源：评论

学校读者我要写书评

暂无评论

Implementation of Summary-Connection-Prediction (SCP) Instructional Strategy in Flipped Classroom with Moodle: Investigate Preservice Teachers' Acceptance and Beliefs 23

Implementation of Summary-Connection-Prediction (SCP) Instru...

引用

8th International Conference on Sustainable information Engineering and technology, SIET 2023

作者： Hariyanti, Uun Batita, Maurish Sofie Rahmi Suharsono, Aswin Department of Information System Faculty of Computer Science Universitas Brawijaya Indonesia

ISBN: (纸本)9798400708503

This study investigated the implementation of summary-connection-prediction (SCP) instructional strategy on students' report tasks before the class under the flipped classroom learning design with Moodle. A total of 106 undergraduate students who enrolled in the Teaching and Learning Theory course participated in this study. A questionnaire based on the technology acceptance model (TAM) and open-ended interview questions were used to collect the data. Following the results, it is known that the preservice teachers have high positive acceptance of SCP strategy. Further, perceived ease of use and perceived usefulness significantly predict behavioral intention, which follows the relationship direction in TAM. Regarding the thematic analysis of interview data, three themes are elaborated to obtain in-depth information about what preservice teachers' beliefs when implementing this strategy. © 2023 ACM.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Opinion mining for stock trend prediction using deep learning

引用

Multimedia Tools and Applications 2024年第19期84卷 21249-21272页

作者： Albahli, Saleh Nazir, Tahira Department of Information Technology College of Computer Qassim University Buraydah Saudi Arabia Faculty of Computing Riphah International University Islamabad Pakistan

Stock market prediction by using Machine Learning (ML) models has been a hot topic of research for more than a decade. Combined with the power of sentiment analysis and ML, social media posts like tweets and financial news can have a big impact on how accurately stock market price predictions are made. Our proposed work makes use of social media posts from Twitter and Google Finance data to predict the price of the stock market using DL techniques. To perform this job, we propose a method that first introduces a concept of fake tweets detection and removal using BERT and then we prepare our dataset using preprocessing techniques. The feature extraction is performed using FastText and VADER, after that the prediction is made through the Deep Belief Network. Two datasets (i.e., Sentiment140 and Twitter real-time data) were used in the experiments and attained 89.12% accuracy along with precision, recall, and F1-Score of 90.15%, 89.12%, and 89.67%. This research not only refines stock market prediction accuracy through a sophisticated blend of sentiment analysis and ML but also introduces novel methodologies in fake tweet detection, feature extraction, and prediction models, charting new territories in the pursuit of precision and reliability. Results reveal that the proposed method performs better in terms of overall accuracy than the most recent methods. We intend to expand the functionality of our approach in the future by including additional well-known social media, such as Facebook and Google News, etc. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Review on Data Visualization Techniques for Real-Time information 7

A Comprehensive Review on Data Visualization Techniques for ...

引用

7th International Conference on Inventive Computation Technologies, ICICT 2024

作者： Choudhary, Vishal Kumar Kumar, Gulshan Suman, Saurabh Kumar, Abhishek Faculty of Engineering And Technology Department of Computer Science And Medical Engineering Maharashtra Wardha India Faculty of Engineering And Technology Department of Computer Science And Design Maharashtra Wardha India

ISBN: (纸本)9798350359299

Research on real-time data visualization methods is necessary to achieve the most accurate and clear representation of information. Creating specific boards and modifying current platforms are two key tasks in performing an appropriate information visualization. An overview of the studies on dashboard platforms, data visualization methods, and accessible strategies is given in this article. To evaluate the effects of the various data visualization approaches on the finished dashboard, a generic and dynamic dashboard based on real-time data was created. Consequently, a preliminary collection of cues, charts, tables, and reports will allow users to interact with the data. produced by the Dashboard itself. Making informed decisions across a variety of businesses requires the capacity to acquire and comprehend real-time information in today's data-driven environment. Real-time data visualization techniques are now essential for turning complex data into insights that can be put to use. This study examines the value of real-time data visualization and offers a summary of strategies and equipment that enable businesses to efficiently use real-time data. © 2024 IEEE.

关键词： Data visualization

来源：评论

学校读者我要写书评

暂无评论

Using ECLAT Algorithm for Privacy Preserving on Publishing Data 3

Using ECLAT Algorithm for Privacy Preserving on Publishing D...

引用

3rd IEEE International Maghreb Meeting of the Conference on sciences and Techniques of Automatic Control and computer Engineering, MI-STA 2023

作者： Omran, Osama M Ben University of Benghazi Faculty of Information Technology Department of Computer Science Benghazi Libya

ISBN: (纸本)9798350319897

many organizations such as online organizations, hospitals, and universities use massive amounts of customer information and use Database systems to enter their data. Many services and benefits are provided by these organizations to the public. The organizations want to publish the data and information for the purpose of research and analysis to obtain many benefits and advantages to improve their work. On the other hand, the data include individuals' sensitive and private information, therefore, organizations are concerned about the security as well privacy;in fact privacy is an important issue when organizations publish their data. This paper suggests a technique to preserve the privacy of the information. The proposed technique uses the ECLAT algorithm which is efficiently mined using the vertical data format. In addition to the ECLAT algorithm, the proposed technique uses some extra steps to process and manage data and to be prepared and secure for publishing. © 2023 IEEE.

关键词： Sensitive data

来源：评论

学校读者我要写书评

暂无评论

Enhanced Speech Emotion and Gender Recognition Using Hybrid CNN-LSTM Models 4

Enhanced Speech Emotion and Gender Recognition Using Hybrid ...

引用

4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Priyadharshini, S. Sundar, G. Naveen Narmadha, D. Thangavel, Senthil Kumar Ajibesin, Adeyemi Abel Kolandapalayam Shanmugam, Selvanayaki Karunya Institute of Technology and Sciences Department of Computer Science and Engineering Coimbatore India Amrita School of Computing Department of Computer Science and Engineering Coimbatore India Cape Peninsula University of Technology Faculty of Informatics and Design Department of Information Technology South Africa Ashland University Department of Mathematics and Computer Science United States

ISBN: (纸本)9798331523923

The current paper proposes a new approach for peripheral speech emotion analysis and gender estimation incorporating the best machine learning architectures such as CNNs and LSTMs. Its correct depiction of emotions and the variation of the gendered speech to indicate manifold signal-to-noise ratio make the approach accommodate the difficulty inherent in recognizing emotions from the recording of voices as well as predicting the gender of a speaker. It is then able to ally with preprocessing and collection of a vast range of different speech samples, feature extraction of pitch, tone and spectral data. These features serve as input to the CNNs and LSTMs: LSTMs work well at temporal regular features and the CNNs work well in feature extraction by location (spatio feature). The approach is tested on the RAVDESS and IEMOCAP datasets and establishes a near perfect match to prior approaches with reference to recognition accuracy of emotion analysis and gender prediction. Thus, applying the identified dual method approach, which could be described by such characteristics as highly accurate data pre-preprocessing, clear indication of the features of interest, a different CNN-LSTM model joint training, it offers a reasonably good platform to gain certain insights into such characteristics of the speech as our experiment demonstrates. This work offers satisfactory configurations on concerns such as human computer relation, customer relation and mental health surveillance to suggest that other applications could be achieved in future. © 2025 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Blockchain and AI Synergy: The SecNet Approach to CPS Data Challenges 8

Blockchain and AI Synergy: The SecNet Approach to CPS Data C...

引用

8th International Conference on Trends in Electronics and Informatics, ICOEI 2025

作者： Kamble, Sohan Gourshettiwar, Palash Faculty of Engineering and Technology Department of Computer Science and Engineering Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Computer Science & Medical Engineering Maharashtra Wardha442001 India

ISBN: (纸本)9798331544607

Cyber, physical, and social (CPS) systems have emerged as the driving force behind today's modern information society, where data is defined as the main capital. information drives almost every technological advancement to amplify industries through artificial intelligence (AI). While data has the potential to enrich an organization, it also presents issues related to privacy, ownership, and security. There are considerable constraints on AI efficiency due to inadequate sensitive sharing frameworks, and the vulnerabilities of individuals' data are not well protected most of the time. This paper presents SecNet, which integrates blockchain and AI to provide a secure mechanism for information exchange between CPSs, thereby enhancing trust, integrity, and productivity. SecNet combines blockchain's distributed ledger with AI's data management skills to protect data and build adequate levels of trust among data users. AI decision-making strength is boosted by SecNet through the provision of high-quality and secure data input, effectiveness in operations, and minimized risks of data sharing. With the help of SecNet, sharing data in CPS systems can become a significant advancement that will stimulate further development and make industries' digital infrastructure more reliable and trustworthy. © 2025 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Smart Agriculture: Enhancing Crop Management through IoT-Based Real-Time Monitoring and Automation 9

Smart Agriculture: Enhancing Crop Management through IoT-Bas...

引用

9th International Conference on information technology and Digital Applications, ICITDA 2024

作者： Paliyanny, Hushalictmy Thinakaran, Rajermani Jalari, Somasekar Neerugatti, Vikram Nalluri, Madhusudana Rao Cholla, Ravindra Raman Inti International University Faculty of Data Science and Information Technology Malaysia Faculty of Engineering and technology Department of Computer Science and Engineering Bangalore India Icfai Foundation for Higher Education Department of Computer Science and Engineering Telangana Hyderabad India

ISBN: (纸本)9798331510732

Internet of Things plays an important role in agriculture in order to provide an innovative and smart solution to traditional farming. IOT is all about connecting physical devices to the internet and can access from a remote place. So that crop monitoring becomes easy even if the farmer is in a remote place. Due to automation, human efforts are required less. Also the IoT data helps the farmer make decisions about planting, harvesting or fertilizing. This paper explains the system we have implemented for monitoring the agriculture with the help of IoT. The system is developed in order to provide real time information on crop conditions to the farmer. For that, it uses various types of sensors connected to the microcontroller in order to measure parameters like temperature, soil moisture, and water level, and accordingly, it activates actuators like a fan, motor or pump to manage ventilation and irrigation. We have used the GSM module to send the alert to the farmer and the WiFi module is used to send the agriculture data to the cloud platform. So that farmer can monitor the farm or crops remotely. The system is continuously collecting farm data from the sensors. If the crop soil is very dry them system will turn on the water pump. Also, for high temperature, the fan will get activated in order to cool down that area. This feature is mostly used in indoor farming. The farmer can monitor the farm condition in real time with the help of cloud platform. This system is helpful for improving productivity, crop management, and save resources i.e. efficient use of water which prevents water wastage. © 2024 IEEE.

关键词： Soil moisture

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

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

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：