A theoretical model for describing the emission spectra of microsphere cavities is presented, and its predictions of detailed lineshapes of emission spectra associated with whispering gallery modes (WGMs) of various o...
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The extreme learning machine (ELM) is known for being a fast learning neural model. This work presents a performance comparison between ELM and the WiSARD weightless neural network model, regarding training and testin...
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We establish an open framework for developing plan optimization models for knowledge-based planning (KBP) in radiotherapy. Our framework includes reference plans for 100 patients with head-and-neck cancer and high-qua...
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Data Envelopment Analysis (DEA) is one method that is often used in the benchmarking process. The benchmarking process with DEA is often faced with problems where there is a Decision Making Unit (DMU) both Input and O...
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Decision-making processes in determining loan eligibility are often subjective which leads to imprecise credit predictions. Due to inaccurate inquiry on prospective customers done by field survey officers of Bank Perk...
Decision-making processes in determining loan eligibility are often subjective which leads to imprecise credit predictions. Due to inaccurate inquiry on prospective customers done by field survey officers of Bank Perkreditan Rakyat (BPR) Bandung City, it has experienced credit complications such as bad credits. Therefore, this study aims to help decision-makers in determining creditworthiness and preventing bad credits from occurring. To realize this solution, the study uses the Fuzzy Logic method to calculate the creditworthiness of each prospective loaner based on the inquiries done in the field survey. Fuzzy Logic is known to be a 'counting' methodology with varying words. In addition, it can implement human expertise into machine language with ease and adequately. Based on numerous testing performed, the results demonstrate a level of 90% in accuracy when inputting within the valid ranges of each fuzzy set and membership function. However, the level of accuracy is only based on the clarification result which is determined by a researcher and BPR director, not a general level of accuracy for other microfinance institutions. Nevertheless, the findings of this study prove the method has a high enough accuracy to support decision-makers in determining the loan eligibility of prospective loaners and through this application in the surveying process, survey workers can work more efficiently. Hence, in future has a higher chance of predicting bad credits from potential loaners.
The Association for the Advancement of Artificial Intelligence 2020 Workshop program included twenty-three workshops covering a wide range of topics in artificial intelligence. This report contains the required report...
This paper proposes a closed-loop sparse channel estimation (CE) scheme for wideband millimeter-wave hybrid full-dimensional multiple-input multiple-output and time division duplexing based systems, which exploits the...
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Background: Physicians invest hours creating patient notes, which are rich in information but difficult for computers to analyze due to their unstructured format. GPT-4 reshaped our ability to process text, yet it is ...
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Background: Physicians invest hours creating patient notes, which are rich in information but difficult for computers to analyze due to their unstructured format. GPT-4 reshaped our ability to process text, yet it is unknown how well this model can handle medical notes. This project aims to compare GPT-4’s ability to annotate medical notes against experienced physicians across three different languages at multiple institutions and countries. Methods: This study included eight sites from four countries - the United States, Colombia, Singapore, and Italy. Each site contributed seven de-identified notes (admission, progress, or consult) from hospitalized patients. GPT-4 assessed each note by answering 14 questions, including demographic information, clinical judgments, data quality, and patients’ eligibility for a hypothetical study enrollment. For validation, two physicians from each site independently evaluated GPT-4's responses. Findings: Overall, 56 medical notes, written in English, Italian, and Spanish, were analyzed. A total of 784 responses from GPT-4 were generated. Both physicians agreed with GPT-4’s response 79% of the time (622/784, 95%CI 76-82%). Only one of the two physicians agreed with GPT-4’s response 10% of the time (82/784, 95%CI 8-13%). Neither physician agreed with GPT-4’s response 10% of the time (80/784, 95%CI 8-13%). Both physicians agreed with GPT-4 more often in notes written in Spanish and Italian than in English, with agreement rates of 88% (86/98, 95%CI 79-93%), 84% (82/98, 95%CI 75-90%), and 77% (454/588, 95%CI 74-80%), respectively. Hallucinations were rare (10/784, 95%CI 0-2%). GPT-4 correctly selected patients for a hypothetical study enrollment based on three criteria 90% of the time (95%CI 81-98%). Interpretation: The findings indicate that GPT-4 annotations demonstrated a high agreement rate with physicians across all languages. We also demonstrate GPT-4's potential to assist in patient selection for studies. Funding: None. Declarati
With advancements in the science of detection and attribution studies, the influence of climate change over many events has now been quantified.Because of the rapidly increasing temperatures, vulnerable populations (a...
With advancements in the science of detection and attribution studies, the influence of climate change over many events has now been quantified.
Because of the rapidly increasing temperatures, vulnerable populations (adults older than 65 years, and children younger than one year of age) were exposed to 3·7 billion more heatwave days in 2021 than annually in 1986–2005 (indicator 1.1.2), and heat-related deaths increased by 68% between 2000–04 and 2017–21 (indicator 1.1.5), a death toll that was significantly exacerbated by the confluence of the COVID-19 pandemic.
Despite the local cooling and overall health benefits of urban greenspaces, only 277 (27%) of 1038 global urban centres were at least moderately green in 2021 (indicator 2.2.3), and the number of households with air conditioning increased by 66% from 2000 to 2020, a maladaptive response that worsens the energy crisis and further increases urban heat, air pollution, and greenhouse gas emissions.
[...]millions of people do not have access to the energy needed to keep their homes at healthy temperatures, preserve food and medication, and meet the seventh Sustainable Development Goal (to ensure access to affordable, reliable, sustainable, and modern energy for all).
Aggravating this situation even further, governments continue to incentivise fossil fuel production and consumption: 69 (80%) of 86 countries reviewed had net-negative carbon prices (ie, provided a net subsidy to fossil fuels) for a net total of US$400 billion
We explore the implementation of a spoof–fluid-spoof (SFS) acoustic waveguide, which is the acoustic analogue of a metal-insulator–metal waveguide in plasmonics. The proposed structure consists of two corrugated rig...
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We explore the implementation of a spoof–fluid-spoof (SFS) acoustic waveguide, which is the acoustic analogue of a metal-insulator–metal waveguide in plasmonics. The proposed structure consists of two corrugated rigid surfaces separated by a fluid layer. The properties of the guided acoustic modes between corrugated rigid parallel plates are analytically and numerically studied by deriving their dispersion relation and through a careful analysis of symmetric and antisymmetric modes supported by this structure. Similar to plasmonic waveguides, it is shown that the dispersion relation of the proposed SFS acoustic waveguide, and the supported group and phase velocities, can be largely controlled by changes in the geometrical parameters of the waveguide, opening the possibility for application of this technology for acoustic delay lines, modulators, and sensors. The analytical and numerical results are validated through experiments in a controlled environment.
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