With the advent of generative artificial intelligence (AI), the scope of data analysis, prediction of performances, real-time feedback, etc. in learning analytics has widened. The purpose of this study is to explore t...
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Fog computing is a key enabling technology of 6G systems as it provides quick and reliable computing,and data storage services which are required for several 6G *** Intelligence(AI)algorithms will be an integral part ...
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Fog computing is a key enabling technology of 6G systems as it provides quick and reliable computing,and data storage services which are required for several 6G *** Intelligence(AI)algorithms will be an integral part of 6G systems and efficient task offloading techniques using fog computing will improve their performance and *** this paper,the focus is on the scenario of Partial Offloading of a Task to Multiple Helpers(POMH)in which larger tasks are divided into smaller subtasks and processed in parallel,hence expediting task ***,using POMH presents challenges such as breaking tasks into subtasks and scaling these subtasks based on many interdependent factors to ensure that all subtasks of a task finish simultaneously,preventing resource ***,applying matching theory to POMH scenarios results in dynamic preference profiles of helping devices due to changing subtask sizes,resulting in a difficult-to-solve,externalities *** paper introduces a novel many-to-one matching-based algorithm,designed to address the externalities problem and optimize resource allocation within POMH ***,we propose a new time-efficient preference profiling technique that further enhances time optimization in POMH *** performance of the proposed technique is thoroughly evaluated in comparison to alternate baseline schemes,revealing many advantages of the proposed *** simulation findings indisputably show that the proposed matching-based offloading technique outperforms existing methodologies in the literature,yielding a remarkable 52 reduction in task latency,particularly under high workloads.
Lie detection has gained importance and is now extremely significant in a variety of fields. It plays an important role in several domains, including law enforcement, criminal investigations, national security, workpl...
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Lie detection has gained importance and is now extremely significant in a variety of fields. It plays an important role in several domains, including law enforcement, criminal investigations, national security, workplace ethics, and personal relationships. As advances in lie detection continue to develop, real-time approaches such as voice stress technology have emerged as a feasible alternative to traditional methods such as polygraph testing. Polygraph testing, a historical and generally established approach, may be enhanced or replaced by these revolutionary real-time techniques. Traditional lie detection procedures, such as polygraph testing, have been challenged for their lack of reliability and validity. Newer techniques, such as brain imaging and machine learning, might offer better outcomes, although they are still in their early phases and require additional testing. This project intends to explore a deception-detection module based on sophisticated speech-stress analysis techniques that might be applied in a real-time deception system. The purpose is to study stress and other articulation cues in voice patterns, to establish their precision and reliability in detecting deceit, by building upon previous knowledge and applying state-of-the-art architecture. The performance and accuracy of the system and its audio aspects will be thoroughly analyzed. The ultimate purpose is to contribute to the advancement of more accurate and reliable lie-detection systems, by addressing the limitations of old techniques and proposing practical solutions for varied applications. This paper proposes an efficient feature-selection strategy, which uses random forest (RF) to select only the significant features for training when a real-life trial dataset consisting of audio files is employed. Next, utilizing the RF as a classifier, an accuracy of 88% is reached through comprehensive evaluation, thereby confirming its reliability and precision for lie-detection in real-time scena
Misinformation is a growing threat to the economy, social stability, public health, democracy, and national security. One of the most effective methods to combat misinformation is fact checking. Fact checking is the p...
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The amortized step complexity of operations on all previous lock-free implementations of double-ended queues is linear in the number of processes. This paper presents the first concurrent double-ended queue where the ...
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Adaptive multicolor filters have emerged as key components for ensuring color accuracy and resolution in outdoor visual ***,the current state of this technology is still in its infancy and largely reliant on liquid cr...
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Adaptive multicolor filters have emerged as key components for ensuring color accuracy and resolution in outdoor visual ***,the current state of this technology is still in its infancy and largely reliant on liquid crystal devices that require high voltage and bulky structural ***,we present a multicolor nanofilter consisting of multilayered‘active’plasmonic nanocomposites,wherein metallic nanoparticles are embedded within a conductive polymer *** nanocomposites are fabricated with a total thickness below 100 nm using a‘lithography-free’method at the wafer level,and they inherently exhibit three prominent optical modes,accompanying scattering phenomena that produce distinct dichroic reflection and transmission ***,a pivotal achievement is that all these colors are electrically manipulated with an applied external voltage of less than 1 V with 3.5 s of switching speed,encompassing the entire visible ***,this electrically programmable multicolor function enables the effective and dynamic modulation of the color temperature of white light across the warm-to-cool spectrum(3250 K-6250 K).This transformative capability is exceptionally valuable for enhancing the performance of outdoor optical devices that are independent of factors such as the sun’s elevation and prevailing weather conditions.
Flapping wing aerial vehicles are nowadays in demand due to surveillance, civil needs, espionage and border missions.A lot of challenges exists in the development of autonomous flight missions for the flapping wing ae...
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This paper investigates how distributed energy resources investment capacities impact the carbon footprint of a renewable energy community. The investigation is conducted through the formulation of an optimisation pro...
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electrical grids are increasingly congested, which causes stability and safety risks. To get more insights in how congestion can be managed, this paper analyses whether bus characteristics exist that have a consistent...
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Capacitive sensing technology is widely applied in ubiquitous sensing. Its low-power consumption enables it to be used in a wide variety of Industry 4.0 applications. Capacitive Sensors can be combined into Arrays (CS...
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