International Journal of Communication Networks and Information Security (IJCNIS)
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THE EFFECTIVENESS OF LEADERSHIP IN IMPROVING THE QUALITY OF HIGHER EDUCATION
No full textThis research aims to realize effective leadership in higher education, presented here is one of the investigations to explore the extent of impact of work planning, providing direction, supervisory activities and the relationship between leaders and subordinates to achieve performance. Data for this study were collected using the qualitative research approach, where it first looked into the general overviews collected through document analysis gathered from reports, brochures, journal articles, newspapers, the Internet, websites and mass media. This research uses a qualitative type, primary data uses interviews, competent informants, namely lecturers, staff and students, the data analysis used is interactive qualitative analysis. The results obtained were significant, effective leadership in higher education, namely the preparation of work programs that involve subordinates, bring benefits to identifying the problems faced. Providing direction that is appropriate to the main tasks and functions has the impact of increasing the professionalism of subordinates. Scheduled and stress-free management activities bring a pleasant work atmosphere. A good relationship between leaders and subordinates can actually produce strength in achieving the vision and mission of higher education. To achieve the vision, mission and goals of higher education institutions, if leaders do not involve subordinates, it is difficult to find out what is hidden. If the direction is not appropriate, it also becomes a problem for subordinates to carry out their tasks well and correctly. Then, supervision is necessary as a step to assess the ability to carry out the duties and work of subordinates. To further support the goals of the institution, a harmonious relationship is needed
Deep Learning-Powered Facial Expression Recognition: Revolutionizing Emotion Detection
No full textFacial expression recognition (FER) is a critical technology with applications spanning healthcare, security, and human-computer interaction. This study explores the development of a sophisticated FER system leveraging deep learning techniques to overcome existing challenges in accuracy, robustness, and practical deployment. The research methodology involved a thorough literature review, selection of quantitative methods for secondary data analysis, and the systematic collection and statistical analysis of data from academic journals and online repositories. The findings highlight the strengths of advanced deep learning architectures, such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), in enhancing FER's accuracy and generalization across diverse datasets. However, challenges related to data privacy, algorithmic biases, and cross-cultural differences remain significant. Despite these obstacles, the study concludes that FER technology, when ethically and responsibly implemented, holds the potential to revolutionize human-computer interaction, healthcare diagnostics, and societal communication. The research contributes to the ongoing discourse on the future of FER by addressing both its technical advancements and ethical implications
The Role of AI in Fortifying Cybersecurity Frameworks
No full textArtificial Intelligence (AI) is revolutionizing the field of cybersecurity by enhancing traditional frameworks and introducing advanced capabilities for threat detection, response, and prediction. This research article explores the multifaceted role of AI in fortifying cybersecurity frameworks, focusing on its integration into established practices and its potential to address rapidly evolving cyber threats. AI algorithms excel in detecting complex patterns and anomalies that elude traditional methods, providing a critical layer of intelligence that speeds up response times and increases accuracy. Moreover, AI's predictive capabilities enable proactive threat management, forecasting potential security breaches before they occur. This paper also discusses the automation of routine tasks, which frees up valuable resources and allows cybersecurity professionals to focus on more strategic initiatives. However, the integration of AI into cybersecurity poses ethical and technical challenges, including concerns about data privacy, algorithmic bias, and the need for continuous system updates and maintenance. Economic considerations also play a significant role, as organizations must weigh the costs against the enhanced security AI promises. By examining these aspects through case studies and expert analyses, this article aims to provide a comprehensive understanding of how AI can be effectively integrated into cybersecurity frameworks, thereby enhancing their effectiveness and resilience against the sophisticated cyber threats of the digital age
Impact of Social Games in Aggregating Relationships in Social Capital through Online Social Media Network
Get PDFIn recent days, social network sites connect people and help them maintain social ties through aggregating and accumulating social capital. This trait is important for organisation and individual success. The literature in the field indicates that there is a wide gap in automating the prediction of aggregation of social capital through online social games in social media networks. The analysis of the impact of social games in facilitating Social Capital (SC) is very vital. The existing mathematical and statistical modelling techniques fail to recognise the inherent and latent associations among the exploratory variables. Hence, this work proposes an ensemble machine learning model that learns the inherent features from the questionnaire collected from online gamers on three genres, namely media technology availability, multimedia communication channels and degree of social connectedness. The base learners explore the data domain in different ways to extract the features. The efficacy of the model's prediction is done by analysing the accuracy, F1 score, precision and recall. The results indicate that the model can effectively classify the instances, whether they positively or negatively contribute to the aggregation of SC. As a future extension of the research, the model can be made to learn more extensive attributes
Mobile Applications Integrated in Blended Learning : A Systematic Literature Review
Get PDFThis systematic literature review explores the use of mobile apps in blended learning, examines the characteristics of the research areas, research objects, and research methods of empirical studies on mobile apps in blended learning, and finally summarizes and organizes the results of the existing empirical studies and suggests implications for future research. This investigation involved a comprehensive search of academic publications within the Web of Science and Scopus databases, focusing on relevant topics. The analysis of the gathered literature indicates that mobile applications serve as efficient, beneficial, and suitable tools for facilitating blended learning. In such learning environments, these applications have the potential to enhance student satisfaction with the course, bolster engagement and motivation, and foster a sense of social connection among learners.However, mobile apps can only be used as an assistive tool for face-to-face learning and cannot replace paper-based assignments or the instructor's guiding role. Future research should attempt to introduce mobile learning apps in blended learning environments and extend the length of experiments to take advantage of mobile apps in order to improve the cognitive depth and breadth of blended learning and engagement
Optimize Urban Infrastructure Planning Based on Big Data and Enhance Xi'an's Urban Image
No full textInfrastructure is an essential support for urban operation, and a city's image is directly related to citizens' quality of life and the city brand's construction. Urban infrastructure distribution, equipment types, network switching, and other issues have always restricted the development of communication in Xi'an City, and the addition of big data technology has further increased the communication pressure in Xi'an City and affected the image of Xi'an City. In this paper, we take Xi'an urban infrastructure as the research object and combine the python method to obtain the big data information in the network and the data in the wireless self-organizing sensor. Then, the incomplete data was eliminated, the data was mapped to the 0~1 interval logarithmic manner, and a standardized processing set was formed. Set up wireless ad hoc sensor devices, collected infrastructure-related data, and summarized data through extensive data analysis. At the same time, based on social urban image data, public demand data, and urban infrastructure evaluation results, the content of urban planning is adjusted to better meet the expectations of the public and provide targeted planning solutions. Finally, according to the data fitting, the matching of wireless ad hoc sensor network and city image improvement is realized, and the reasonable planning of infrastructure is promoted. The results of urban image analysis show that wireless ad hoc sensor networks and big data technology can simplify the steps of urban infrastructure planning, reduce urban planning costs, enhance the functionality of the infrastructure, reduce the public complaint rate, and meet the requirements of Xi'an urban image improvement
The Role of Wireless Network Technology in Analysis of Audience Satisfaction of Chinese Web Dramas in the Big Data Era
Get PDFThe continuous development of Wireless network technology has made web dramas popular on a large scale and made the cause of web dramas popular become the focus of research on mobile communication and modern communication. As an essential component of media effect research, analysis of the Audience Satisfaction plays a significant role in web drama research. However, the original click-through rate measurement method can not effectively solve the problem of analyzing the Audience Satisfaction of web dramas in the era of big data, and the accuracy of cause analysis is low. Therefore, this paper proposes an analysis model based on wireless network technology to analyze the popular Audience Satisfaction of web dramas from the perspective of the uses and gratifications theory. Firstly, wireless network technology is used to summarize the data transmission rate of web dramas, and judgment is made according to the popular methods, and reasons for data characteristics, and irrelevant popular data of web dramas is discarded. Then, the results are analyzed according to the data transmission rate and data form of the web drama and compared with the click-through rate measurement method to find out the reasons for the possibility of existence. After simulation test and analysis, Wireless network technology can improve the accuracy of judging the Audience Satisfaction of web dramas, with an accuracy rate of 90.3%, judge the reasons for different types of web drama content and forms, and calculate the cause analysis time, and find that this method can meet the cause analysis of web dramas Multifaceted needs
Improve Privacy-Preserving for User Identity: Possibilities, Challenges, and Future Directions
Get PDFElectronic payment via mobile devices has become the modern way of payment. While facilitating and speeding up many payment processes, this method also brings about certain crucial problems related to electronic payment where the users fear putting the security of their bank accounts and personal information at risk in electronic payment operations. Electronic payment services do not fully secure personal accounts and may be subjected to violations. Yet compared to traditional offline mode payment channels, mobile payments are transforming the supply chain of businesses and sectors and are crucial to the rapid expansion of online markets. The kind of mobile payment channel utilized, the security infrastructure that accompanies it, the stakeholders engaged, and the m-business models chosen all have a role in the success of an e-business. However, concerns about preserving the identity and privacy of users, referred to by users as sensitive information, should not be dealt with via the Internet. In this study, we describe the most recent research in this field and give a thorough literature review of mobile payment
Research on Flood Disaster Monitoring and Early Warning Technology Based on UAV Remote Sensing and AI Algorithm
No full textThis paper, based on UAV far-flung sensing science and synthetic brain algorithm, studies the monitoring and early warning technological know-how of flood catastrophes. Firstly, the far-flung sensing monitoring science of flood catastrophes is summarized. Then, blended with geographic records machine (GIS) technology, the UAV far-flung sensing science software in flood catastrophe monitoring is analyzed. Finally, combining the micro-UAV technological know-how and AI technology, the key applied sciences of the micro-UAV flood catastrophe monitoring and early warning device primarily based on AI imaginative and prescient are studied, along with the lookup of the micro-UAV key gadget and the lookup of AI imaginative and prescient key technology. The key device lookup of micro-UAV is the definition of mindset. Mindset A mindset lookup on key applied sciences of AI, imaginative and prescient broadly speaking, expounds the precept of CNN and introduces Faster RCNN. It lays the groundwork for the later lookup on flood catastrophe monitoring and early warning technological know-how primarily based on UAV far-off sensing and AI algorithms
Reliability and Precision of Digital Forensic Tools and Software: A Systematic Review Study
No full textDigital forensics is important discipline to study and analyze the digital evidence for legal reasons. Assessment of the reliability and accuracy of digital forensic tools and software is essential for the integrity and performance of digital investigations. In this regard, digital forensic tools and software have acquired the status of indispensable for proper manipulation and analysis of digital data in the light of the fact that digital forensics is a dynamically developing sphere. These may involve examination of the tool’s underlying algorithms, examination of its error rates, testing of its compatibility with different file formats, assessment of its user-friendliness and evaluation of its compliance with standards and best practices in the field. Furthermore, the evaluation includes the vendor’s reputation and the track record in the field of developing digital forensic tools. Although digital forensic tools have a very important task of identifying and convicting crimes in the court, they are subject to misuse which may lead to unreliable results. Forensic experts most of the time choose tools not because of their effectiveness but just because such tools are available, cost- effective, and familiar to them among other things thus making tools to be unreliable. Resulting in failure of the entire criminal investigation procedure, leaving criminals unpunished and even at risk for repeated offenses. The research intends to offer an understanding of digital forensic tools for the detection and mitigation of information and cybercrimes, stressing its capability as a powerful defense against emerging threats in the system