Background: Intensified research and innovation and rapid uptake of new tools, interventions, and strategies are crucial to fight Tuberculosis, the world's deadliest infectious disease. The sharing of health data ...
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While various models and computational tools have been proposed for structure and property analysis of molecules, generating molecules that conform to all desired structures and properties remains a challenge. Here, w...
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Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitati...
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Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze continued...challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative
Network Function Virtualization (NFV), as a promising paradigm, speeds up the service deployment by separating network functions from proprietary devices and deploying them on common servers in the form of software. A...
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Dynamic processes on networks, be it information transfer in the Internet, contagious spreading in a social network, or neural signaling, take place along shortest or nearly shortest paths. Unfortunately, our maps of ...
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OBJECTIVEThis paper aims to describe the image retakes program over several decades, and identify the causes of issues due to rejection rates. MATERIALS & METHODSThis study is a literature review using the Preferr...
OBJECTIVEThis paper aims to describe the image retakes program over several decades, and identify the causes of issues due to rejection rates. MATERIALS & METHODSThis study is a literature review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method. Articles were searched from Google Scholar (3140) and Scopus (18) using keywords " Reject" or " Repeat" or " Retakes" and " Analysis" and " in" and " Diagnostic" and " Imaging". The article range was expanded to describe the profile of repeat analysis from the use of film-screen to digital transformation systems. Based on the established criteria, 20 articles were extracted and analyzed. RESULTSFrom the literature, it was found that repeat rates above 5% were still found in some examination categories, with chest radiography contributing the highest rejection rate, reaching 51.67%, with the biggest contributing factor being positioning (84.8%). There are interesting findings related to this program, where subjective factors in determining the classification of rejection causes still exist. One study mentioned that AI can predict image rejection accuracy with a sensitivity of 93%. Therefore, the use of AI can be very helpful in classifying rejection causes, making data available for more efficient and easier radiology management. CONCLUSIONRepeat program is part of image quality management. The justification for rejection decisions still poses a challenge related to personnel's subjective factors and determining the causes of rejection/repeat must also be done to obtain concrete data related to radiography performance.
Recently, the use of unmanned aerial vehicles (UAVs) as a relay node has been envisaged as an enabling technology in the upcoming wireless communication era. Thus, in this paper, we consider a full-duplex (FD) coopera...
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Progress in artificial intelligence (AI), particularly deep reinforcement learning (RL), has produced systems capable of performing at or above a professional-human level. This research explored the ability of RL to t...
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ISBN:
(数字)9781728145334
ISBN:
(纸本)9781728145341
Progress in artificial intelligence (AI), particularly deep reinforcement learning (RL), has produced systems capable of performing at or above a professional-human level. This research explored the ability of RL to train AI agents to achieve optimal offensive behavior in small tactical engagements. Agents were trained in a simple, aggregate-level military constructive simulation with behaviors validated with the tactical principles of mass and economy of force. Results showed the combat model and RL algorithm applied had the largest impact on training performance. Additionally, specific training hyper-parameters also contributed to the quality and type of observed behaviors. Future work will seek to validate RL performance in larger and more complex combat scenarios.
The Brimob Corps is a special police force, just like the special military detachments held by the TNI such as Paskhas and so on. At present brigade corps police national is busy being discussed in the real world and ...
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Strongly enhanced electron-electron interaction in semiconducting moiré superlattices formed by transition metal dichalcogenides (TMDCs) heterobilayers has led to a plethora of intriguing fermionic correlated sta...
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