J. Mobile Multimedia最新文献_第2页

Telemonitoring of Human Biomedical and Biomechanical Signals 人体生物医学和生物力学信号的远程监测

J. Mobile Multimedia Pub Date : 2023-02-15 DOI: 10.13052/jmm1550-4646.19310

B. Shevchuk, O. Ivakhiv, O. Zastavnyy, M. Geraimchuk

引用次数: 0

Hate Speech Detection in Social Media (Twitter) Using Neural Network 基于神经网络的社交媒体(Twitter)仇恨言论检测

J. Mobile Multimedia Pub Date : 2023-02-15 DOI: 10.13052/jmm1550-4646.1936

Ara Miran, H. Yahia

{"title":"Hate Speech Detection in Social Media (Twitter) Using Neural Network","authors":"Ara Miran, H. Yahia","doi":"10.13052/jmm1550-4646.1936","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.1936","url":null,"abstract":"Hate speech recently became a real threat in social media, and almost all social media users are intended to in different ways. Hate speech is not limited to a group or society. It affects many people and can be classified as abusive, offensive, sexism, racism, political affiliation, religious hate, nationality, skin color, disability, gender-based, ethnicity, sexual orientation, immigrants, and others. Many researchers and authorities attempt to discover new procedures to sense hate speech in social media, especially on Facebook and Twitter, and many methods, models, and algorithms are used for this purpose. One of the most valuable models for detecting hate speech is Convolutional Neural Network (CNN). This review aims to assort academic studies on hate speech detection in Twitter using CNN-based models summarize the results of each model to expand the understanding of the recent circumstances of hate speech detection in Twitter. For this purpose, we implemented a broad, automated search using Boolean and Snowballing searching methods to find academic works in this area. Studies and papers have been distinguished, and the following information was obtained and aggregated from each article: authors, publication’s year, the journal name or the conference name, proposed model/method, the aim of the study, the outcome, and the quality of each study. According to the findings, the CNN and CNN-based models are standard models for hate speech detection. Besides, the findings show that other new models have a great compact on hate speech detection, and there is good progress in this field. However, the problems that still exist with hate speech detection models mainly are; most of the models cannot detect hate speech automatically. The methods are not suitable with all the languages, and they are working only with one language; most are best suited with the English language, and when they are used with datasets with other languages. Besides, the models are suffering from confusion in speech classification. Finally, most models are not considering a user-to-user speech in social media.","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134602032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing Cloud Forensic Investigation System in Distributed Cloud Computing Using DK-CP-ECC Algorithm and EK-ANFIS 利用DK-CP-ECC算法和EK-ANFIS增强分布式云取证系统

J. Mobile Multimedia Pub Date : 2023-02-15 DOI: 10.13052/jmm1550-4646.1933

Shaiqa Nasreen, A. H. Mir

{"title":"Enhancing Cloud Forensic Investigation System in Distributed Cloud Computing Using DK-CP-ECC Algorithm and EK-ANFIS","authors":"Shaiqa Nasreen, A. H. Mir","doi":"10.13052/jmm1550-4646.1933","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.1933","url":null,"abstract":"The investigation as well as recovery of data gathered as of digital devices associated with computer crime is involved in Digital Forensics (DF). In a distributed Cloud Server (CS), DF investigation is more complicated (during collecting, preserving, and reporting the evidence) as well as insecure during gathering evidence as of the cloud sources. Centered on the DF investigation system, numerous works were performed. However, lots of challenges still remain that bring about cybercrime. The work developed a robust cloud forensic investigation system centered upon distributed Cloud Computing (CC) for conquering the challenges. It is framed into the ‘3’ phase (i.e.) originally, Group Key Generation (GKG) phase that enables the authorized user to upload or download the evidence for maintaining the evidence’s trustworthiness. Distributed Key Cipher Policy Elliptic Curve Cryptography (DK-CP-ECC) algorithm performed the Secure Data Transfer (SDT) phase. It aids in maintaining the evidence’s privacy together with confidentiality. Exponential Membership Function Adaptive Neuro-Fuzzy Interference System (EK-ANFIS) carries out the CS selection with the aid of a deer hunting genetic algorithm that evades the reporting issues and renders secure evidence storage. 97% Security Level (SL) is obtained by the proposed work that is better analogized to the prevailing frameworks.","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117157733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Queue's Automated Creation of Doctor's Calls by Patients in the Hospital with Visualization via the Mobile Application 通过移动应用程序可视化医院中患者自动创建医生呼叫队列

J. Mobile Multimedia Pub Date : 2023-02-15 DOI: 10.13052/jmm1550-4646.19311

I. Zhuravska, M. Dvoretskyi, I. Kulakovska, Anzhela P. Boiko, S. Dvoretska

{"title":"The Queue's Automated Creation of Doctor's Calls by Patients in the Hospital with Visualization via the Mobile Application","authors":"I. Zhuravska, M. Dvoretskyi, I. Kulakovska, Anzhela P. Boiko, S. Dvoretska","doi":"10.13052/jmm1550-4646.19311","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.19311","url":null,"abstract":"The spread of the COVID-19 virus is challenging society to provide medical care to a growing number of patients in the hospital. It is important to determine the patient from whom an urgent appeal was received earlier and to automate the creation of the calls’ queue. Determining the direction of the sound source, which is the patient’s voice, can be realized using the passive acoustic location method. In this case, it is necessary to place sound sensors in the wards with patients. In such a case, these sensors it is expedient to build in the lighting equipment executed in the shape of Platonic polyhedra. The microcontroller system, located inside such a spatial structure, ensures the transmission of sound to a server computer system. The above system alternately records the receipt of urgent appeals, analyzes the location of the sound source, and sends the relevant data to the doctor’s smartphone. The mobile application visualizes information about the location of the patients who need consultation or help. The proposed solution for intelligent analysis of voice appeals by inpatients may also be useful for post-stroke, post-infarction, and other bedridden patients who are unable to call medical staff otherwise than a voice.","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124812034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

6G Intelligent Healthcare Framework: A Review on Role of Technologies, Challenges and Future Directions 6G智能医疗框架:技术作用、挑战与未来方向综述

J. Mobile Multimedia Pub Date : 2023-02-15 DOI: 10.13052/jmm1550-4646.1931

S. Kharche, J. Kharche

{"title":"6G Intelligent Healthcare Framework: A Review on Role of Technologies, Challenges and Future Directions","authors":"S. Kharche, J. Kharche","doi":"10.13052/jmm1550-4646.1931","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.1931","url":null,"abstract":"The Healthcare industry is experiencing a sea change due to the availability of disruptive communication technologies. Augmented reality, virtual reality, haptics, robotic assistance, and the ubiquitous, highly reliable low latency communication based on intelligence; support remote surgery in real-time. The sixth-generation (6G) mobile communication supporting disruptive technologies and intelligence; will realize remote healthcare for people of all ages in three-dimensional (3D) space. The discussion on the application of disruptive technologies in 6G intelligent healthcare is found insufficient in the literature. The objective of the paper is to propose a conceptual framework for 6G intelligent healthcare and elaborate on applications of the various disruptive technologies with their associated challenges. The state-of-the-art technologies viz; digital twin, blockchain, optical wireless communication, wireless energy transfer, tactile Internet, holographic communication, quantum communication, artificial intelligence, etc., are elaborated for their applications and challenges in healthcare. The fifth-generation (5G) lacks supporting disruptive technologies, intelligence, and ultra-low latency requirements of remote healthcare. 6G will support highly reliable (99.9999%), secure, ultra-low latency (<0.1 microseconds), and ultra-high-speed communication (>1 Tbps) required for remote and ubiquitous healthcare. Moreover, 6G supports the Internet of Everything, Internet of skills, and Internet of thinking to realize and optimize healthcare globally.","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116335883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Universal Design for an Adaptive Context-Aware Mobile Cloud Learning Framework Using Machine Learning 使用机器学习的自适应上下文感知移动云学习框架的通用设计

J. Mobile Multimedia Pub Date : 2023-02-15 DOI: 10.13052/jmm1550-4646.1934

Aiman M. Ayyal Awwad

{"title":"A Universal Design for an Adaptive Context-Aware Mobile Cloud Learning Framework Using Machine Learning","authors":"Aiman M. Ayyal Awwad","doi":"10.13052/jmm1550-4646.1934","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.1934","url":null,"abstract":"Mobile learning is becoming more and more popular today. It gained popularity recently due to the COVID-19 pandemic restrictions in 2020. However, to provide learners with appropriate educational materials in such a mobile environment, the characteristics and context of the learners must be considered. Therefore, in this paper, we propose a framework for providing an adaptive context-aware learning process considering a combination of student learning models and principles of Universal Design for Learning (UDL). The proposed system consists of components capable of detecting changes in context and adapting the way the application responds and behaves. The framework uses a machine-learning algorithm to predict learners’ characteristics and follow UDL principles to deliver enriched user experience and location-aware content and activities. An online survey was conducted with 20 undergraduate students. We analyzed their levels of satisfaction with the proposed m-learning system. From the analyzed data, we noticed that the average rating values are close to 4.5, which indicates that the proposed m-learning system complies with UDL principles and provides an adaptive and localized learning environment, thus enhancing the efficiency of the learning process and experiences. The study also investigated the impact of factors (i.e., noise level, physical activity, and location) on learners’ concentration towards the learning process. The results show that these factors have a significant impact on the learner’s concentration level.","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121958024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Implementation of Generative Adversarial Networks in Mobile Applications for Image Data Enhancement 生成对抗网络在图像数据增强移动应用中的实现

J. Mobile Multimedia Pub Date : 2023-02-15 DOI: 10.13052/jmm1550-4646.1938

Oleksandr Striuk, Yuriy Kondratenko

引用次数: 0

Swarm Optimization of Fuzzy Systems for Mobile Robots with Remote Control 移动机器人远程控制模糊系统的群优化

J. Mobile Multimedia Pub Date : 2023-02-15 DOI: 10.13052/jmm1550-4646.1939

O. Kozlov, Y. Kondratenko, O. Skakodub, O. Gerasin, A. Topalov

{"title":"Swarm Optimization of Fuzzy Systems for Mobile Robots with Remote Control","authors":"O. Kozlov, Y. Kondratenko, O. Skakodub, O. Gerasin, A. Topalov","doi":"10.13052/jmm1550-4646.1939","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.1939","url":null,"abstract":"This paper is dedicated to the development and research of the advanced approach for optimization of fuzzy control systems (FCS) for mobile robots (MR) with remote control based on bioinspired swarm techniques. The proposed approach makes it possible to create effective intelligent control systems for MRs based on the principles of hierarchical multi-level control, remote IoT-based control, fuzzy logic control, and intelligent optimization of fuzzy control devices. The applied hybrid particle swarm optimization (PSO) techniques with elite strategy allow effectively optimizing various parameters of FCSs, finding the optimal solution to the problem, and, at the same time, have a higher convergence rate compared with the basic PSO algorithms. To evaluate the effectiveness of the obtained advanced approach based on hybrid swarm techniques, the optimization process of the FCS for the speed control of the multi-purpose caterpillar MR, which can move on inclined and vertical ferromagnetic surfaces, is carried out. The presented research results fully confirm the high efficiency of the proposed approach, as well as the expediency of its application for the optimization of fuzzy control systems for various remotely controlled mobile robots.","PeriodicalId":425561,"journal":{"name":"J. Mobile Multimedia","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130187727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Identity - Attribute Inference in Online Social Network(s) Using Bio-Inspired Algorithms and Machine Learning Approaches 使用生物启发算法和机器学习方法的在线社交网络中的身份-属性推断

J. Mobile Multimedia Pub Date : 2023-02-15 DOI: 10.13052/jmm1550-4646.1932

Nisha P. Shetty, Balachandra, D. R. Teja, L. Maben, Tummala Srinag Vinil

引用次数: 0

Human Motion Capture Data Retrieval and Segmentation Technology for Professional Sports Training 面向专业运动训练的人体动作捕捉数据检索与分割技术

J. Mobile Multimedia Pub Date : 2022-11-15 DOI: 10.13052/jmm1550-4646.1923

Hui Chen

引用次数: 1