851 research outputs found

    Somatic Coliphage PHIX174 Inactivation Kinetics, Mechanisms and Modeling in Surface Waters

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    Ph.DDOCTOR OF PHILOSOPH

    Federated Learning in Competitive EV Charging Market

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    Federated Learning (FL) has demonstrated a significant potential to improve the quality of service (QoS) of EV charging stations. While existing studies have primarily focused on developing FL algorithms, the effect of FL on the charging stations' operation in terms of price competition has yet to be fully understood. This paper aims to fill this gap by modeling the strategic interactions between two charging stations and EV owners as a multi-stage game. Each station first decides its FL participation strategy and charging price, and then individual EV owners decide their charging strategies. The game analysis involves solving a non-concave problem and by decomposing it into a piece-wise concave program we manage to fully characterize the equilibrium. Based on real-world datasets, our numerical results reveal an interesting insight: even if FL improves QoS, it can lead to smaller profits for both stations. The key reason is that FL intensifies the price competition between charging stations by improving stations' QoS to a similar level. We further show that the stations will participate in FL when their data distributions are mildly dissimilar.Comment: Accepted to IEEE ISGT EUROPE 202

    TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series

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    This work summarizes two strategies for completing time-series (TS) tasks using today's language model (LLM): LLM-for-TS, design and train a fundamental large model for TS data; TS-for-LLM, enable the pre-trained LLM to handle TS data. Considering the insufficient data accumulation, limited resources, and semantic context requirements, this work focuses on TS-for-LLM methods, where we aim to activate LLM's ability for TS data by designing a TS embedding method suitable for LLM. The proposed method is named TEST. It first tokenizes TS, builds an encoder to embed them by instance-wise, feature-wise, and text-prototype-aligned contrast, and then creates prompts to make LLM more open to embeddings, and finally implements TS tasks. Experiments are carried out on TS classification and forecasting tasks using 8 LLMs with different structures and sizes. Although its results cannot significantly outperform the current SOTA models customized for TS tasks, by treating LLM as the pattern machine, it can endow LLM's ability to process TS data without compromising the language ability. This paper is intended to serve as a foundational work that will inspire further research.Comment: 10 pages, 6 figure

    Convergence of regional economic cycles in Turkey

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    Dissimilar economic fluctuations and asymmetric shocks across the regions of a country might create severe policy distortions that, under these circumstances, aggregate policy interventions (such as taxation and interest rates), are likely to be sub-optimal for at least a fraction of the regions. For instance, monetary policy can hardly satisfy the needs of all regions when some of the regions are experiencing a boom while others are in a recession phase. For these reasons, similarity of regional business cycles and their convergence are highly desirable from a policy viewpoint. The aim of this paper is, therefore, to provide empirical evidence and policy implications in that context. In particular, I analyze business cycle correlations across Turkish provinces and the tendency of these cycles to converge over the period of analysis between 1975-2000 and 2004-2008 (for Nomenclature of Territorial Units for Statistics [NUTS]-2 regions). I find that regional business cycle asymmetries have tended to decrease in recent decades. This result, although it seems to provide evidence in favor of rising correlations, shows that the convergence process is rather slow and there still exist asymmetries across the regional business cycles

    AFP-Net: Realtime Anchor-Free Polyp Detection in Colonoscopy

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    Colorectal cancer (CRC) is a common and lethal disease. Globally, CRC is the third most commonly diagnosed cancer in males and the second in females. For colorectal cancer, the best screening test available is the colonoscopy. During a colonoscopic procedure, a tiny camera at the tip of the endoscope generates a video of the internal mucosa of the colon. The video data are displayed on a monitor for the physician to examine the lining of the entire colon and check for colorectal polyps. Detection and removal of colorectal polyps are associated with a reduction in mortality from colorectal cancer. However, the miss rate of polyp detection during colonoscopy procedure is often high even for very experienced physicians. The reason lies in the high variation of polyp in terms of shape, size, textural, color and illumination. Though challenging, with the great advances in object detection techniques, automated polyp detection still demonstrates a great potential in reducing the false negative rate while maintaining a high precision. In this paper, we propose a novel anchor free polyp detector that can localize polyps without using predefined anchor boxes. To further strengthen the model, we leverage a Context Enhancement Module and Cosine Ground truth Projection. Our approach can respond in real time while achieving state-of-the-art performance with 99.36% precision and 96.44% recall

    Spatial-temporal pattern and influencing factors of tourism ecological security in Huangshan City

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    It is of important theoretical and practical value to scientifically evaluate tourism ecological security for the sustainable development of tourist cities. The study focuses on the “characteristics of the impact factors on tourism ecological security at different levels” of tourism ecological security that have been neglected in the previous literature. From the perspective of Compound Ecological systems theory, we built an evaluation index system for tourism ecological security in Huangshan City based on the Pressure-State-Impact-Economic-Environmental-Social (PSR-EES) model and used a combination of the entropy weight TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method, traditional and spatial Markov chains, and panel quantile regression to analyze and characterize the spatial-temporal dynamics of security levels and driving factors. The results showed that (1) the level of tourism ecological security of the districts and counties in Huangshan City improved rapidly, but the difference was expanding. The level of tourism ecological security in the four counties was generally higher than that in the three districts. (2) In terms of the spatial-temporal dynamic evolutionary characteristics, the transfer of tourism ecological security in Huangshan City has its characteristics of stability and path dependence. Type transfers usually occur between adjacent levels. The lower the level of tourism ecological security, the higher the probability of upward transfer. A neighborhood background plays an important role in the process by which a higher neighborhood rank increases the probability of upward transfer. (3) Regarding the driving factors, environmental pollution and economic development have a negative inhibitory effect on tourism ecological security, and the negative effect decreases as the level of TES improves. The top three positive effects were government intervention and educational levels. The degree of regional greening and government intervention had greater positive marginal effects on lower-level areas. In contrast, tourism development, educational level, and labor input had greater positive marginal effects on areas with higher TES levels
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