Attending to one’s voice in a cocktail party is notably challenging, particularly for individuals with hearing impairments. This paper proposes a novel eye-controlled target speaker extraction system, which consists ...
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ISBN:
(数字)9798350364194
ISBN:
(纸本)9798350364200
Attending to one’s voice in a cocktail party is notably challenging, particularly for individuals with hearing impairments. This paper proposes a novel eye-controlled target speaker extraction system, which consists of an eye-tracker, face detection model, Active Speaker Detection (ASD), and Target Speaker Extraction (TSE) model. The system employs the eye-tracker to capture real-time video together with the listener’s gaze. This gaze data then allows the face detection model to locate and isolate the target speaker’s face within the video on a frame-by-frame basis. Using the speaker’s face as the reference cue, the system can discern and separate his/her speech from a mixture of multi-talk. The experiments show that the system effectively extracts the target speaker’s speech in complex auditory environments, providing both real-time performance and accuracy. A demonstration of our system is available on our website
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Malware scanning of an app market is expected to be scalable and effective. However, existing approaches use syntax-based features that can be evaded by transformation attacks or semantic-based features which are usua...
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The rapid advancement of digital technologies has underscored the critical necessity for robust and reliable identity verification systems in today's interconnected world. Traditional centralized identity manageme...
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ISBN:
(数字)9798350376685
ISBN:
(纸本)9798350376692
The rapid advancement of digital technologies has underscored the critical necessity for robust and reliable identity verification systems in today's interconnected world. Traditional centralized identity management systems encounter myriad challenges, from vulnerabilities to data breaches and privacy concerns, to inefficiencies inherent in verification processes. This paper delves into the transformative potential of decentralized identity verification systems using blockchain technology as a robust solution to these pressing issues. By harnessing blockchain's immutable, transparent, and secure characteristics, decentralized identity systems not only promise enhanced privacy, security, and user control over personal data but also foster a paradigm shift towards more efficient and user-centric identity management *** study rigorously examines the foundational principles of blockchain technology and its strategic application in decentralized identity verification. It highlights key opportunities such as strengthened security measures through cryptographic protocols, enhanced user autonomy in managing and sharing personal information, and streamlined verification processes that reduce operational complexities and costs. Additionally, the paper critically evaluates significant challenges that must be addressed, including scalability concerns as blockchain networks grow, complexities in navigating regulatory landscapes designed for centralized systems, and overcoming barriers to widespread user adoption. Through an exhaustive analysis of existing models, real-world case studies, and emerging trends, this paper aims to provide comprehensive insights into the feasibility and future prospects of decentralized identity verification systems. By contributing to the ongoing discourse on innovative identity management solutions in the digital age, this research seeks to pave the way for more secure, efficient, and equitable digital ecosystems.
With the widespread application of digital assets and the rapid development of blockchain technology, achieving secure and efficient transactions between different blockchain networks has become an urgent challenge. E...
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Autism Spectrum Disorder (ASD) is a developing disorder if the symptoms develop obvious in the initial years of age but it could be present in some age groups. ASD is mental health problem that affects communicational...
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This paper explores the innovative data As Partner (DAP) philosophy as a transformative approach to organisational data strategy, drawing upon established concepts of information value, technology acceptance, and incl...
This paper explores the innovative data As Partner (DAP) philosophy as a transformative approach to organisational data strategy, drawing upon established concepts of information value, technology acceptance, and inclusivity for people with disabilities (PwD) in smart cities. The study conducted a comprehensive systematic review, after meticulous screening, 20 eligible papers were selected, forming the foundation for deriving the key components of the DAP framework. Subsequently, a qualitative focus group study engaged 18 participants from diverse sectors to evaluate the practical applicability of the DAP conceptual framework. Thematic analysis of the focus group sessions revealed five key themes: practical value, pragmatic performance, ethical perspective, clarity of the framework, and enhancement tools. These findings offer valuable insights for refining the DAP framework and optimising its integration into real-world scenarios, in empowering individuals in smart cities, especially those with disabilities. Future research should explore larger and more diverse samples to generalise findings and assess the framework's long-term impact through longitudinal evaluations. By adopting user-centred methodologies, the DAP framework can be further enhanced as a strategic tool, empowering data to actively participate in organisational decision-making processes.
In recent years, privacy and security concerns have led to the wide adoption of encrypted protocols, making encrypted traffic a major portion of overall communications online. The transition into more secure protocols...
In recent years, privacy and security concerns have led to the wide adoption of encrypted protocols, making encrypted traffic a major portion of overall communications online. The transition into more secure protocols poses significant challenges for internet service providers to utilize traditional traffic classification techniques in order to guarantee the Quality of Service (QoS), Quality of Experience (QoE), and cyber-security of their customers. In this work, we introduce two methods, namely STFT-TC and DWT-TC, leveraging compact time-series representation coupled with well-known techniques from the field of Digital Signal Processing (DSP): the short-time Fourier transform (STFT) and the discrete wavelet transform (DWT). The STFT-TC method extracts a suite of statistical and spectral features from the magnitude spectrogram, offering a fresh perspective on interpreting and classifying encrypted traffic. The DWT-TC method extracts statistical features from the wavelet coefficients and incorporates unique characteristics that describe the signal's shape and energy distribution. Evaluating our methods on two public QUIC datasets demonstrated improvements in accuracy of up to 5.7%. Similarly, the F1-scores also showed enhancements, with increments of up to 5.9% for the same datasets.
Internet of Things (IoT) based Bridge Structural Health Monitoring (BSHM) is a hot topic in the field of civil engineering and computerscience, and has been widely concerned by academia and industry. The lifetime of ...
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The wide spread of rumors[3] on social media has caused a negative impact on people's daily life, leading to potential panic, fear and mental health problems for the public.[47] How to debunk rumors as early as po...
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Marine debris, the majority of which is composed of plastic (61 % to 87 %), is a significant environmental issue facing the world. Between 4.8 million and 12.7 million metric tons of plastic are thought to have entere...
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ISBN:
(数字)9798350365191
ISBN:
(纸本)9798350365207
Marine debris, the majority of which is composed of plastic (61 % to 87 %), is a significant environmental issue facing the world. Between 4.8 million and 12.7 million metric tons of plastic are thought to have entered the ocean in 2010 alone, increasing the estimated total amount of particles in the water to at least 5 trillion. Global plastic production, which reached 348 million tons in 2017, is expected to double in the next 20 years. To overcome this challenge, effective waste detection methods are needed, one of which is by utilizing computer vision, specifically the You Only Look Once (YOLO) algorithm. YOLOv9, as the latest version, offers improved object detection performance compared to its predecessor, YOLOv8. This research aims to evaluate the performance and efficiency of YOLOv9 and YOLOv8 in detecting marine waste. Using the Trash Annotations in Context dataset (TACO), We train both models and conduct tests to evaluate their accuracy and efficiency. Experimental results show that YOLOv9 has higher precision at 45% but lower recall at 6%, compared to YOLOv8, which has a precision of 33 % and a recall of 15 %. Overall, YOLOv8 shows better performance with higher mAP50 at 13% and mAP50-95 values at 10%, compared to YOLOv9, which has mAP50 at 4% and mAP50-95 values at 3%.
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