检索结果-内蒙古大学图书馆

Digital forensics for the socio-cyber world (DF-SCW): A novel framework for deepfake multimedia investigation on social media platforms

引用

Egyptian Informatics Journal 2024年 27卷

作者： Ayub Khan, Abdullah Chen, Yen-Lin Hajjej, Fahima Ahmed Shaikh, Aftab Yang, Jing Soon Ku, Chin Yee Por, Lip Department of Computer Science and Information Technology Benazir Bhutto Shaheed University Lyari Sindh Karachi75660 Pakistan Department of Computer Science Sindh Madressatul Islam University Sindh Karachi74000 Pakistan Department of Computer Science and Information Engineering National Taipei University of Technology Taipei106344 Taiwan Department of Software Engineering College of Computer and Inf. Sci. Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia Department of Computer System and Technology Faculty of Computer Science and Information Technology Universiti Malaya Kuala Lumpur50603 Malaysia Department of Computer Science Universiti Tunku Abdul Rahman Kampar31900 Malaysia

Owing to the major development of social media platforms, the usage of technological adaptation increases by means of editing software tools. Posting media in social communication environments has become one of our common daily routines. Before posting, various editing generators are used to manipulate pixel values, such as for enhancing brightness and contrast. Undoubtedly, this software helps bring posting media from ordinary to outstanding. But such a type of editing crosses the line in terms of creating fakes—anything that comes from anywhere and does not retain its originality anyway. It poses a series of issues in the process of multimedia forensics investigation and chain of custody. In order to restrict the attempts at deep faking and make the investigation hierarchy more effective, efficient, and reliable in the socio-cyber space (SCS), this paper presents a novel framework called DF-SCW. A digital forensics-enabled socio-cyber world with artificial intelligence (AI), especially deep neural networks (DNNs), for detecting and analyzing deep fake media investigations on social media platforms. It compares pixels with their neighboring values in the same media (such as images and videos) to identify information about the original one. There is a media flag designed to filter out malicious and dangerous attempts, like a powerful leader declaring war. Putting flags on such fakes helps digital investigators resist sharing the posts. In addition, the other prospect of this research is to make the digital forensics ecosystem more appropriate to take qualitative judgments in real-time while media is uploaded on social media platforms. The simulation of the proposed DF-SCW is tested on three different platforms, such as Instagram, Facebook, and Twitter. Through the experiment, the DF-SCW outperformed in terms of detection, identification, and analysis of deepfake media by an increased rate of 3.77%. © 2024

关键词： Social networking (online)

来源：评论

学校读者我要写书评

暂无评论

Study on collaborative filtering recommendation algorithm based on prediction for item rating

Study on collaborative filtering recommendation algorithm ba...

引用

2020 International Conference on engineering Management of Communication and technology, EMCTECH 2020

作者： Xiao, Shaozhang Ling, Haonan Lu, Yi Tang, Zhaoxia Faculty of Computer and Software Engineering Huaiyin Institute of Technology Huai'an Jiangsu China

ISBN: (数字)9781728196688

ISBN: (纸本)9781665404488

As the Internet is developing rapidly and people are becoming increasingly dependent on e-commerce, whether the users can be provided with accurate recommendation information has become the key to attracting users. Under this background, corresponding personalized recommendation systems have been proposed, and collaborative filtering algorithm is one of the algorithms commonly used in the recommendation systems. Collaborative filtering recommends the information in which the user is interested through analyzing the preferences of a group with similar interests and common experience. With the increasing number of users and items in the e-commerce system, the collaborative filtering algorithm is limited by data sparsity in operation, which will influence the quality of the recommendation results. This paper studied the collaborative filtering recommendation algorithm based on the prediction for item rating, and enhanced the accuracy of the recommendation algorithm by designing an improved similarity-based algorithm for predicting ratings based on the Pearson correlation coefficient. © 2020 IEEE.

关键词： Collaborative filtering

来源：评论

学校读者我要写书评

暂无评论

Ant: An Efficient Lossless Compression Algorithm for IoT Time Series Data

Ant: An Efficient Lossless Compression Algorithm for IoT Tim...

引用

IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Junhui Li Guangping Xu Hongzhang Yang Yulei Wu School of Computer Science and Engineering Tianjin University of Technology Tianjin China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin China Key Laboratory of Computer Vision and System Ministry of Education China Faculty of Science and Engineering University of Bristol Bristol U.K

In various applications in Internet of Things like industrial monitoring, large amounts of floating-point time series data are generated at an unprecedented rate. Efficient compression algorithms can effectively reduce the size of data, enhance transmission performance and storage efficiency, and simultaneously lower storage costs. Therefore, there is a need for lightweight and efficient stream compression algorithms. In this paper, we propose a novel lossless floating-point data compression algorithm called Ant. The main idea is to encode double-precision floating-point numbers into integer form, calculate the delta between adjacent values, and then convert the delta into unsigned integers. This encoding method effectively reduces storage costs and improves data compression efficiency. Extensive experiments on real-world datasets demonstrate that our algorithm achieves compression speeds at least as fast as state-of-the-art streaming methods, and a 63% relative improvement in average compression rate.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Low level Syntax Elements Study in Intra HEVC/H.265 Video Codec 7

Low level Syntax Elements Study in Intra HEVC/H.265 Video Co...

引用

7th International Conference on Image and Signal Processing and their Applications, ISPA 2022

作者： Menasri, Wahiba Meddah, Karim University of Sciecnes and Technology Houari Boumediene Usthb Laboratory of Image Processing and Radiation Algiers Algeria University Yahya Fares of Medea Nouveau Pôle Urbain Faculty of Technology Medea Algeria Polytechnique Montréal Motce Laboratory Department of Computer and Software Engineering MontrealQC Canada Usthb Laboratory of Instrumentation Department of Electrical Engineering Algiers Algeria

ISBN: (纸本)9781665480420

Ultra High Definition Television (UHDTV) imposes extremely high throughput requirement on video encoders based on High Efficiency Video Coding (H.265/HEVC). HEVC adopt many advanced developed techniques in order to compress and decompress the video sequence for ensuring the real time requirements with keeping the quality. The decoded video is obtained according to the syntax elements language specified by the HEVC standard. Consequently, HEVC adopt 74 syntax elements at the low level which are divided into four partitions: including quad tree partitioning, intra and inter prediction, transform level, quantization and loop filtering. This work propose a profound study of HEVC low level syntax elements. The four partitions of syntax elements are defined, detailed and specified (role). After that, the encoding process and order of each syntax element is given by diagram blocks followed by an examples of encoding process syntax elements for 4x4 and 8x8 transform blocks (references blocks) by using Matlab ***, performance comparison of different benchmarks is given in order to highlights the decoding efficiency of HEVC compared it predecessor AVC (Advenced Video Coding). This work give the only detailed study that demonstrate the main functionality of the all intra syntax elements encoding process in CABAC HEVC. © 2022 IEEE.

关键词： MATLAB

来源：评论

学校读者我要写书评

暂无评论

A Deep Learning Framework for Arabic Cyberbullying Detection in Social Networks

引用

computers, Materials & Continua 2025年第5期83卷 3113-3134页

作者： Yahya Tashtoush Areen Banysalim Majdi Maabreh Shorouq Al-Eidi Ola Karajeh Plamen Zahariev Computer Science Department Jordan University of Science and TechnologyIrbid22110Jordan Department of Information Technology Faculty of Prince AI-Hussein Bin AbdallahⅡFor Information TechnologyThe Hashemite UniversityZarqa13133Jordan Computer Science Department Tafila Technical UniversityTafila6110Jordan Department of Digital Media Software Engineering Ferris State UniversityBig RapidsMI 49503USA Department of Telecommuniations University of Ruse“Angel Kanchev”Ruse7017Bulgaria

Social media has emerged as one of the most transformative developments on the internet,revolu-tionizing the way people communicate and ***,alongside its benefits,social media has also given rise to significant challenges,one of the most pressing being *** issue has become a major concern in modern society,particularly due to its profound negative impacts on the mental health and well-being of its *** the Arab world,where social media usage is exceptionblly high,cyberbullying has become increasingly prevalent,necessitating urgent *** detection of harmful online behavior is critical to fostering safer digital environments and mitigating the adverse efcts of *** underscores the importance of developing advanced tools and systems to identify and address such behavior *** paper investigates the development of a robust cyberbullying detection and classifcation system tailored for Arabic comments on *** study explores the efectiveness of various deep learning models,including Bi-LSTM(Bidirectional Long Short Term Memory),LSTM(Long Short-Term Memory),CNN(Convolutional Neural Networks),and a hybrid CNN-LSTM,in classifying Arabic comments into binary classes(bullying or not)and multiclass categories.A comprehensive dataset of 20,000 Arabic YouTube comments was collected,preprocessed,and labeled to support these *** results revealed that the CNN and hybrid CNN-LSTM models achieved the highest accuracy in binary classification,reaching an impressive 91.9%.For multiclass dlassification,the LSTM and Bi-LSTM models outperformed others,achieving an accuracy of 89.5%.These findings highlight the efctiveness of deep learning approaches in the mitigation of cyberbullying within Arabic online communities.

关键词： Arabic text lassification arabic text mining cyberbullying detection neural networks deep learning CNN LSTM YouTube Bi-LSTM

来源：评论

学校读者我要写书评

暂无评论

Design of Face Recognition Attendance 5

Design of Face Recognition Attendance

引用

5th IEEE International Conference on Image, Vision and Computing, ICIVC 2020

作者： Lee, Hai-Wu Gu, Wen-Tan Wang, Yuan-Yuan Huaiyin Institute of Technology Faculty of Computer and Software Engineering Huaian City China

ISBN: (纸本)9781728166612

In recent years, face recognition technology has developed rapidly, and its application range has become more and more extensive. It is one of the most important application fields in computer vision technology. However, there are still many technical factors that restrict the application and promotion of face recognition technology. For example: shadows, occlusions, light and dark areas, dark light, highlights and other factors will make the face recognition rate drop sharply. Therefore, face recognition has extremely high research and application value. We use the Local Binary Patterns (LBP) algorithms with histogram equalization to obtain high-resolution images and improve the recognition rate in different scenarios, and try to apply face recognition to attendance. © 2020 IEEE.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

A Novel Gooseneck Barnacle Optimizer Based Machine Learning Approach for Rainfall Prediction

A Novel Gooseneck Barnacle Optimizer Based Machine Learning ...

引用

Sustainable Technologies for Industry 4.0 (STI), International Conference on

作者： Marzia Ahmed Mohd Herwan Sulaiman Mostafijur Rahman Ahmad Johari Mohamad Faculty of Electrical & Electronics Engineering Technology Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA) Pahang Malaysia Department of Software Engineering Daffodil International university Dhaka Bangladesh Department of Computer Science and Engineering Green University of Bangladesh

In dynamic meteorological prediction, accurate rainfall forecasting is a mystery. In a complex and dynamic natural environment with unpredictable sky movements, we propose an innovative methodology that forecasts weekly average rainfall patterns using the Gooseneck Barnacle Optimizer and the Least Squares Support Vector Machine (LSSVM). The significance of rainfall prediction is shown by its widespread implications, including public health. However, conventional single-model techniques and machine-learning methods must represent rainfall pattern changes, limiting our preparation. With a 2014–2018 dataset from reliable meteorological libraries, our research explores the possibility of this novel combination. The Gooseneck Barnacle Optimizer (GBO) serves as the bedrock of our methodology, introducing a novel evolutionary algorithm inspired by the intricate mating behaviors of gooseneck barnacles. GBO aptly captures the dynamic interplay of factors such as navigational sperm casting properties, food availability, food attractiveness, wind direction, and intertidal zone wave movement during mating, culminating in two crucial optimization stages: exploration and exploitation. In contrast to previous algorithms like the Barnacle Mating Optimizer (BMO), GBO stands out by more accurately emulating the unique mating behaviors of gooseneck barnacles. The prediction job is performed by integrating the Least Squares Support Vector Machines (LSSVM) algorithm with GBO as an objective function, using the optimized hyper-parameter values. The results suggest that the GBO algorithm exhibits superior performance compared to existing methodologies. This is accomplished by efficiently augmenting the original random population for a particular problem, resulting in a convergence towards the global optimum and producing significantly enhanced optimization outcomes.

关键词：

来源：评论

学校读者我要写书评

暂无评论

The Low-Cost IoT Mornitoring the Quality of River: A Case Study of Wang River in Lampang Municipality

The Low-Cost IoT Mornitoring the Quality of River: A Case St...

引用

International computer Science and engineering Conference (ICSEC)

作者： Narong Krueganta Oran Chieochan Anukit Saokaew Ekkachai Yana Chaowoot Singkaew Weerachai Sawangtook Ekkarat Boonchieng Warakhom Wongchai Sakchai Srimakorn Faculty of Industrial Technology School of Industrial Technology Lampang Rajabhat University Lampang Thailand Faculty of Sciences School of Information Technology Lampang Rajabhat University Lampang Thailand Faculty of Science School of Environmental innovation Lampang Rajabhat University Lampang Thailand Faculty of Industrial Technology School of Computer Engineering Lampang Rajabhat University Lampang Thailand Department of Computer Sciences Faculty of Sciences Chiang Mai University Chiang Mai Thailand Faculty of Industrial Technology School of Industrial Electrical Engineering Lampang Rajabhat University Lampang Thailand Faculty of Industrial Technology School of Software Engineering Lampang Rajabhat University Lampang Thailand

The research project focuses on prototyping an IoT (Internet of Things) system for measuring and monitoring the quality of the Wang River in Lampang Municipality. The system utilizes EC (Electrical Conductivity), pH, and temperature sensors connected to an ESP32 microcontroller with a custom-developed board. Additionally, the IoT system is supported by a solar cell system to provide power. The software programming is implemented using Arduino C++ on the PlatformIO platform, which is integrated with Visual Studio code. The IoT platform chosen for this project is ThingsBoard, specifically the community version. The research findings indicate that the utilization of IoT technology combined with the sensors has improved the prototype of a low-cost IoT monitoring system for assessing the quality of the Wang River in Lampang Municipality.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Application of Nonlinear Gaussian Process Regression Models for CO2 Emissions Prediction

Application of Nonlinear Gaussian Process Regression Models ...

引用

International Conference on Innovations in Information technology

作者： Ahmed Abdelhadi Ahmed Yousif Badri Asaad Shamseldin Department of Computer Science & Software Engineering College of Information Technology (CIT) United Arab Emirates University Al Ain UAE Department of Mechanical and Mechatronics Engineering Faculty of Engineering University of Auckland Auckland New Zealand Department of Civil and Environmental Engineering Faculty of Engineering University of Auckland Auckland New Zealand

The growing concern over climate change led to a massive corpus of literature addressing the impact of various factors in terms of carbon dioxide (CO2) emissions levels. However, the majority of existing literature employs linear models to a singular factor, neglecting the relation of these factors and their impact in conjunction on CO2 emissions levels. To answer this question, this study conducted an intensive literature review to identify proper factors to deduce parameters that influence CO2 emissions levels. These parameters, derived from data spanning from 1965 to 2021 in the United Arab Emirates, underwent thorough analysis using Dominance Analysis to establish their significance in relation to CO2 emissions levels. Subsequently, we employed nonparametric nonlinear Gaussian Process Regression (GPR) models with diverse kernels to assess their performance against traditional parametric linear models. The results showed that nonparametric nonlinear GPR models provide the most accurate predictions for CO2 emissions, with the GPR-Matern kernel outperforming all other models, achieving an R-squared value of 98.1%. Our findings highlight the importance of adopting a nonlinear approach for predicting and forecasting CO2 emissions levels when considering the interplay of driving factors.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Towards Eco-Sustainability and Green Analytics Model to Measure the Performance of Big Data Systems

Towards Eco-Sustainability and Green Analytics Model to Meas...

引用

International Conference on Information Management (ICIM)

作者： Yusmadi Yah Jusoh Rusli Abdullah Rozi Nor Haizan Nor Jamaiah Hj. Yahaya Shireen Muhammad Aishwharya Raani Arunachalam Dept. of Software Engineering and Information Systems Faculty of Computer Science and Information Technology Universiti Putra Malaysia Serdang Malaysia Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Bangi Malaysia Faculty of Communication Visual Art and Computing Universiti Selangor (UNISEL) Selangor Malaysia

Many BDS is doomed to failure because of the missing knowledge on measuring the performance of BDS. The failure to identify the performance measurement and correct will make the problems worsen. This will complicate the efforts of fixing such problems and more importantly, will affect the quality of knowledge, insights, and results expected by the users in the future. In achieving durable performance, the organization needsto understand the factors that contribute to the performance of the eco-sustainability and green analytics metrics for BDS. Although the existence of its importance and awareness was largely neglected. Therefore, the eco-sustainability and green analytic measurement of the BDS is examined in this research. Measuring the BDS performance has the benefit of identifying problems and launching corrective actions before these problems happen and become worsen. The research will investigate the eco-sustainability and green analytic measures which will be proposed and used to capture performance for each process of BDS. Then, based on such measures and metrics, as well as existing performance concepts, frameworks, and models, a measurement model for BDS will be created. The model will be validated through expert evaluations and confirmatory studies with users and practitioners of BDS users. The research has a greater significance in leveraging existing performance concepts in BDS settings and the research proposes users' participation in the sustainability and continuous performance evaluation of theirBDS.

关键词：

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：