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The results show that accurate profiling is achievable, although cyber-profiling on Facebook by no means can represent the full scope of cyber-profiling.
Summary Sending and receiving text messages on cell phones is increasingly common.
Proceedings ArticleDOI
Wei Fan, Kai-Hau Yeung 
09 Aug 2010
12 Citations
And virus will spread faster in Facebook network if users of Facebook spend more time on it for entertainment.
Proceedings ArticleDOI
07 Apr 2015
13 Citations
Results showed a successful detection of cyber events.
Open accessJournal ArticleDOI
Phillip Nyoni, Mthulisi Velempini 
19 Citations
Findings indicate that users’ personal data can be obtained as they are publicly available on Facebook.

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Why optical coherence tomography images are superior to retinal fundus images?
4 answers
Optical Coherence Tomography (OCT) images are superior to retinal fundus images due to their ability to provide detailed information crucial for diagnosing diabetic retinopathy (DR) and other retinal disorders. OCT angiography (OCT-A) allows for quantification of parameters like macular vascular density and foveal avascular zone, aiding in early detection and treatment monitoring of DR. Studies show that OCTA exhibits consistency with fundus fluorescein angiography (FFA) in diagnosing DR, overcoming FFA limitations and enabling quantification of retinal changes post-treatment. Enhanced OCT models, utilizing deep learning algorithms, enhance the specificity and accuracy of retinal OCT classification, crucial for precise diagnosis and therapeutic evaluation. Additionally, OCT demonstrates higher sensitivity and specificity compared to non-mydriatic fundus photography in detecting DR and macular edema, making it a superior screening tool.
Question about skills of the Students?
5 answers
Students today need to acquire a diverse set of skills to thrive in the modern educational and professional landscape. The international educational policies outlined by UNESCO, OECD, and the European Commission emphasize the importance of digital and social skills, lifelong learning culture, citizenship, and ecology learning for students and educators alike. Additionally, the assessment of ICT skills among undergraduate students reveals a gap between perceived and actual skill levels, highlighting the need for students to sharpen their IT skills before entering the workforce, while universities should encourage the application of IT knowledge and skills. Furthermore, research on ninth-grade students suggests that developing questioning skills through informative texts is crucial for their educational advancement, emphasizing the significance of questioning abilities at different educational stages.
How does entity matching with graph techniques improve the accuracy of named entity recognition in natural language processing?
4 answers
Entity matching with graph techniques enhances the accuracy of named entity recognition in natural language processing by leveraging syntactic structures and semantic information. By utilizing a graph-based approach, such as the Syntactic-Informed Graph Network (SIGN), multiple syntactic structures of input sentences are integrated into a heterogeneous matching graph, allowing for the interaction of word semantics and syntactic information to collectively enhance matching accuracy. Additionally, incorporating graph learning and graph attention mechanisms enables the representation and interaction of various types of information within the model, leading to improved performance in identifying entities. These techniques address the limitations of traditional sequence labeling methods, allowing for more comprehensive entity recognition, including nested entities, and achieving state-of-the-art results in both flat and nested entity datasets.
Whats the electricity demand and cost of a typical Pit Thermal Energy Storage system for district heating
4 answers
The electricity demand and cost of a typical Pit Thermal Energy Storage (TES) system for district heating can vary based on different scenarios and system configurations. Research indicates that the introduction of TES, such as pit and tank storage systems, can significantly impact the operation and cost-effectiveness of district heating systems. In one study, the cost of storing waste heat using a borehole TES system was estimated to be between 34 and 41 MSEK, with a payback period of 7 to 9 years, supplying 14 GWh/year during winter months. Additionally, the introduction of short-term TES in a district energy system led to a reduction in individual electricity costs for heat consumers (11.5% to 37.5%) and a decrease in electricity consumption (~-13%) due to improved system efficiency.
How do hybrid healthcare models compare to traditional models in terms of cost-effectiveness and efficiency?
5 answers
Hybrid healthcare models, combining face-to-face consultations with telemedicine, have shown promise in various studies. In the context of rheumatoid arthritis patients during the COVID-19 pandemic, a hybrid care modality was found to be non-inferior to traditional in-person consultations in achieving patient-reported outcomes. Additionally, in healthcare education, the development of cost-effective and configurable hybrid simulation platforms has been highlighted as beneficial for educators to simulate different scenarios effectively. These platforms, utilizing standardized patients and wearable/web-based technologies, have demonstrated effectiveness in enhancing student learning outcomes and confidence in handling real-world healthcare scenarios, indicating their potential for improving cost-effectiveness and efficiency in healthcare training and education.
What are the criticisms of hexaco?
5 answers
Critics of the HEXACO model have raised concerns regarding its distinctiveness from other personality models like the Big Six model, highlighting differences in trait measurements and predictive power. Additionally, research on the Dark Triad suggests that there may be more malevolent traits beyond the HEXACO factors, indicating potential limitations in capturing all dark personality traits. Furthermore, a study on trust behavior in adolescents found no significant evidence supporting the HEXACO dimensions as predictors of trust behavior, suggesting a potential lack of association between HEXACO traits and behaviors during adolescence. These criticisms underscore the need for further research to explore the limitations and boundaries of the HEXACO model in capturing the full spectrum of personality traits and behaviors.
What is the social trust measurement in political ?
5 answers
Social trust measurement in political contexts is a crucial aspect that has seen advancements in recent research. Studies have highlighted the interdependencies between social and political trust, emphasizing the importance of fair institutions and societal networks in trust-building. Comparisons of political and interpersonal trust measurements have been conducted, revealing similar effects of socio-demographic variables on both types of trust. Additionally, the accuracy and comparability of social and political trust measurements across different time periods have been examined, showing stability over time with exceptions in specific years. These insights contribute to understanding the complexities of measuring social trust within political frameworks, shedding light on the factors influencing trust perceptions in society and politics.
What are the failures of fuzzy tests based on deep learning?
10 answers
Fuzzy tests based on deep learning, while innovative and powerful, exhibit several failures and limitations across different implementations and applications. One of the primary failures is the Seq2Seq model's inability to effectively handle unstructured cases, which limits its fuzz testing performance and bug detection capabilities in such scenarios. Additionally, mutation-based fuzz testing techniques, particularly those applied to deep neural networks (DNNs), often suffer from a lack of diversity and distribution deflection from the original DNN input space. This deficiency impacts the comprehensive evaluation of DNNs' robustness against adversarial vulnerabilities. Moreover, existing testing approaches for deep learning (DL) libraries fail to comprehensively exercise these libraries, as they primarily utilize existing trained models and focus only on the model inference phase. This approach overlooks potential bugs in the model training phase, thereby limiting the detection of bugs within DL libraries. In the context of testing DL inference engines, the lack of attention to the core underlying frameworks and libraries, as opposed to the DL models themselves, represents another failure. This oversight misses opportunities to improve the quality of DL systems through more targeted fuzz testing methods. Regression fuzzing techniques, such as DRFuzz, although designed to find regression faults in evolving DL systems, may not always guarantee the fidelity of generated test inputs, which is crucial for accurately identifying diverse regression faults. Furthermore, some approaches to enhancing input examples for testing DL systems suffer from low generalization ability across different models and neglect deep feature constraints, which are essential for maintaining the semantic integrity of adversarial examples. Lastly, the application of mutation-based fuzzing for augmenting DNN training data, aimed at enhancing robustness, is challenged by the optimization problem of generating the most suitable input data variant for training, which can complicate the augmentation process and potentially slow down training.
Should social media allow Anonymous Accounts?
5 answers
Social media platforms should consider reframing anonymity as pseudonymity to balance freedom of expression and prevent harm. Anonymity can lead to cyberstalking issues due to the ease of creating multiple accounts. To address this, a proposed solution involves allowing unlinkable and disclose posting, ensuring accountability without compromising anonymity. Additionally, the rise of fake accounts on social media, like Twitter, has led to the spread of spam and misinformation, highlighting the importance of detecting and addressing such accounts. Therefore, while social media can benefit from allowing some level of anonymity for user privacy and freedom of expression, platforms must implement measures like pseudonymity and spam detection to mitigate potential harms and misuse.
How does IoT technology contribute to the efficiency and effectiveness of home security systems?
5 answers
IoT technology significantly enhances the efficiency and effectiveness of home security systems by enabling seamless communication between devices. Through IoT, smart devices like cameras, sensors, and alarms can detect intruders, fire accidents, and gas leakages, providing real-time alerts to homeowners via SMS, email, or notifications. This technology allows for continuous monitoring, multi-sensing operations, and immediate responses to security threats, ensuring a proactive approach to home security. Additionally, IoT facilitates remote access to home appliances and security systems, enabling users to control and monitor their homes from anywhere via the internet. By integrating IoT capabilities, home security systems become more cost-effective, efficient, and capable of addressing various security challenges, ultimately enhancing the safety and protection of homeowners.
How to apply recommendation system to library management?
5 answers
To apply a recommendation system to library management, one can leverage data from users' borrowing history and feedback, as seen in various research papers. Utilizing Content Based (CB) and Collaborative Filtering (CF) approaches can enhance the system's performance, with CF showing up to a 47% improvement in relevant recommendations. Additionally, integrating information from online social communities like Anobii can enrich user readings for CF and provide richer book metadata for CB, further enhancing recommendation accuracy. Implementing intelligent recommendation algorithms, such as deep learning models, can significantly improve user experience by offering tailored suggestions based on user preferences and behaviors. By identifying users' information needs and recommending relevant literature through AI-based recommendation systems, libraries can streamline information retrieval, enhance user satisfaction, and optimize library services effectively.