Leishmaniases are a group of tropical and neglected diseases caused by the protozoa of the genus Leishmania which are transmitted by insect sandflies. Despite of the major efforts undertaken at global level for the co...
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The way 5G operators manage infrastructure, enterprise and customers will be radically different compared to preceding generations. This paper aims to provide new perspectives on the 5G operating model by presenting a...
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With recent advances in artificial intelligence (AI) and robotics, unmanned vehicle swarms have received great attention from both academia and industry due to their potential to provide services that are difficult an...
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Early detection of infants with autism spectrum disorder (ASD) can lead to effective developmental support. In clinical practice, early screening of 18-month-old infants is implemented using a parent-completed questio...
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ISBN:
(数字)9798331531614
ISBN:
(纸本)9798331531621
Early detection of infants with autism spectrum disorder (ASD) can lead to effective developmental support. In clinical practice, early screening of 18-month-old infants is implemented using a parent-completed questionnaire. However, research has suggested that signs of ASD may also appear in movement characteristics during the first few months of age. In this paper, we propose a method to evaluate infant movement from videos based on non-negative tensor factorization (NTF) and apply it to ASD risk assessment in the neonatal period. The proposed method applies NTF to pose data estimated from videos, and decomposes the infant’s movements into multiple components while considering the linkage between body parts. In the experiment, we evaluated the effectiveness of the proposed method using 36 low-risk infants and 13 high-risk infants for ASD, with the aim of applying the method to ASD risk assessment. The results showed that the proposed method captured the tendency for infants to perform different movements depending on their risk level. Machine learning analysis revealed that the proposed method identified ASD risk with an accuracy exceeding 70%, which was comparable or superior to the existing video evaluation method based on heuristically designed indicators.
This paper aims to identify what new features need to be improved in the IoT services implemented in the Jakarta Smart City platform. We use sequential steps to construct the Kano Model and first define 10 attributes ...
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Over the past few years, a tremendous change has occurred in computer-Aided diagnosis (CAD) technology. The evolution of numerous medical imaging techniques has enhanced the accuracy of the preliminary analysis of sev...
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Before implementing 5G technology, each operator first needs to know their existing network capability. The operator's network must be able to meet the stringent 5G network requirements, including a very low laten...
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Due to excessive nutrient enrichment and rapidly increasing water demand, the occurrence of riverine environment deterioration events such as algal blooms in rivers of China has become more frequent and severe since t...
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Due to excessive nutrient enrichment and rapidly increasing water demand, the occurrence of riverine environment deterioration events such as algal blooms in rivers of China has become more frequent and severe since the 1990s, which has imposed harmful consequences on riverine ecosystems. However, tackling river algal blooms as an important issue of restoring riverine environment is very challenging because the complex interaction mechanisms between the causes are impacted by multiple factors. The contributions of our study consist of: (1) optimizing joint operation of water projects for boosting synergies of water quality and quantity, and hydroelectricity;and (2) preventing algal bloom from perspectives of hydrological and water-quality conditions by regulating water releases of water projects. This study proposed a multi-objective optimization methodology grounded on the Non-dominated Sorting Genetic Algorithm to simultaneously minimize the excess values of algal bloom indicators (water quality, O1), minimize the used reservoir capacity for water supply (water quantity, O2), and maximize the hydropower generation (hydroelectricity, O3). The proposed methodology was applied to several catastrophic algal bloom events that took place between 2017 and 2021 and thirteen water projects in the Hanjiang River of China. The results indicated that the proposed methodology largely stimulated the synergistic benefits of the three objectives by reaching a 36.7% reduction in total nitrogen and phosphorus concentrations, a 33.1% improvement in the remaining reservoir capacity, and a 41.0% improvement in hydropower output, as compared with those of the standard operation policy (SOP). In addition, the optimal water release schemes of water projects would increase the minimum streamflow velocity of downstream algal bloom control stations by 8.6%–9.4%. This study provides a new perspective on water project operation in the environmental improvement in big river systems while boost
Virtual assistants are improving and providing consumers with greater advantages. The comprehension and fulfilment of requests by virtual assistants will increase as voice recognition and natural language processing c...
Virtual assistants are improving and providing consumers with greater advantages. The comprehension and fulfilment of requests by virtual assistants will increase as voice recognition and natural language processing continue to grow. Virtual assistants are projected to be employed in more commercial activities as speech recognition technology advances. The main goal of developing personal assistant software (virtual assistant) is to use web-based semantic data sources, user-generated content, and knowledge from knowledge libraries. Basically, main objective of making this Voice-Based Virtual Assistant is to make life easier and having a personal assistant to everyone which can perform many tasks. As the end user interacts with a virtual assistant, the AI programming learns from the data provided and improves its ability to forecast the end user's needs. Virtual assistants are often used to do things like add tasks to a calendar, provide information that would normally be found in a website, and operate and monitor Smart Home devices like lighting and cameras and thermostats. Massive volumes of data are required to fuel virtual assistant technologies, which feed Artificial Intelligence (AI) platforms such as machine learning, natural language processing, and speech recognition. Speech recognition has a lengthy history and has seen several key advancements. On smartphones and wearable devices, speech recognition for dictation, search, and voice commands has become a standard feature. Design of a small, large vocabulary speech recognition system that can run quickly, accurately, and with minimum latency on mobile devices.
The World Economic Forum has developed the Energy Architecture Performance Index (EAPI) to help nations or regions gain insights into the status of energy systems, with the goal of Steering energy systems to be more a...
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