scholarly journals Bike-Sharing Fleet Allocation Optimization Based on Demand Gap and Cycle Rebalancing Strategies

2022 ◽  
Vol 2022 ◽  
pp. 1-14
Author(s):  
Jianhua Cao ◽  
Weixiang Xu ◽  
Wenzheng Wang
Keyword(s):  
Optimization Model ◽  
Consumer Demand ◽  
Time Interval ◽  
Decision Variable ◽  
Initial Number ◽  
Single Cycle ◽  
On Demand ◽  
Bike Sharing ◽  
Fleet Allocation

In Bike-Sharing System (BSS), the initial number of bikes at station will affect the time interval and the amount of rebalancing, which is usually empirically determined and does not reflect the characteristics of consumer demand in finer time granularity, thus possibly leading to biased conclusions. In this paper, a fleet allocation method considering demand gap is first proposed to calculate the initial number of bikes at each station. Then, taking the number of demand gap periods as the decision variable, an optimization model is built to minimize the total rebalancing amount. Furthermore, the research periods are divided into multiple subcycles, the single-cycle and multicycle rebalancing strategies are presented, and the additional subcycle rebalancing method is introduced to amend the number of bikes between subcycles to decrease the rebalancing amount of the next subcycle. Finally, our methods are verified in effectively decreasing the rebalancing amount in a long-term rebalancing problem.

Enhancing the power generation of Rhodopseudomonas palustris-based MFC

2020 ◽  
Vol 64 (1-4) ◽  
pp. 1261-1268
Author(s):  
Shu Otani ◽  
Dang-Trang Nguyen ◽  
Kozo Taguchi
Keyword(s):  
Activated Carbon ◽  
Rhodopseudomonas Palustris ◽  
Ozone Treatment ◽  
Maximum Power Density ◽  
On Demand ◽  
Long Time ◽  
Dry Conditions ◽  
Carbon Sheet ◽  
Uv Ozone

In this study, a portable and disposable paper-based microbial fuel cell (MFC) was fabricated. The MFC was powered by Rhodopseudomonas palustris bacteria (R. palustris). An activated carbon sheet-based anode pre-loaded organic matter (starch) and R. palustris was used. By using starch in the anode, R. palustris-loaded on the anode could be preserved for a long time in dry conditions. The MFC could generate electricity on-demand activated by adding water to the anode. The activated carbon sheet anode was treated by UV-ozone treatment to remove impurities and to improve its hydrophilicity before being loaded with R. palustris. The developed MFC could generate the maximum power density of 0.9 μW/cm2 and could be preserved for long-term usage with little performance degradation (10% after four weeks).

scholarly journals Inferring Long-Term Demand of Newly Established Stations for Expansion Areas in Bike Sharing System

2021 ◽  
Vol 11 (15) ◽  
pp. 6748
Author(s):  
Hsun-Ping Hsieh ◽  
Fandel Lin ◽  
Jiawei Jiang ◽  
Tzu-Ying Kuo ◽  
Yu-En Chang
Keyword(s):  
New York ◽  
Feature Extraction ◽  
Real World ◽  
Extraction Methods ◽  
Real World Data ◽  
Urban Dynamics ◽  
Bike Sharing ◽  
The Government ◽  
Short Time

Research on flourishing public bike-sharing systems has been widely discussed in recent years. In these studies, many existing works focus on accurately predicting individual stations in a short time. This work, therefore, aims to predict long-term bike rental/drop-off demands at given bike station locations in the expansion areas. The real-world bike stations are mainly built-in batches for expansion areas. To address the problem, we propose LDA (Long-Term Demand Advisor), a framework to estimate the long-term characteristics of newly established stations. In LDA, several engineering strategies are proposed to extract discriminative and representative features for long-term demands. Moreover, for original and newly established stations, we propose several feature extraction methods and an algorithm to model the correlations between urban dynamics and long-term demands. Our work is the first to address the long-term demand of new stations, providing the government with a tool to pre-evaluate the bike flow of new stations before deployment; this can avoid wasting resources such as personnel expense or budget. We evaluate real-world data from New York City’s bike-sharing system, and show that our LDA framework outperforms baseline approaches.

scholarly journals A Novel Deep Learning Approach for Machinery Prognostics Based on Time Windows

2019 ◽  
Vol 9 (22) ◽  
pp. 4813 ◽  
Author(s):  
Hanbo Yang ◽  
Fei Zhao ◽  
Gedong Jiang ◽  
Zheng Sun ◽  
Xuesong Mei
Keyword(s):  
Time Windows ◽  
Remaining Useful Life ◽  
Sensor Data ◽  
Time Interval ◽  
Kernel Module ◽  
Initial Stage ◽  
Research Task ◽  
Consecutive Time ◽  
Useful Life

Remaining useful life (RUL) prediction is a challenging research task in prognostics and receives extensive attention from academia to industry. This paper proposes a novel deep convolutional neural network (CNN) for RUL prediction. Unlike health indicator-based methods which require the long-term tracking of sensor data from the initial stage, the proposed network aims to utilize data from consecutive time samples at any time interval for RUL prediction. Additionally, a new kernel module for prognostics is designed where the kernels are selected automatically, which can further enhance the feature extraction ability of the network. The effectiveness of the proposed network is validated using the C-MAPSS dataset for aircraft engines provided by NASA. Compared with the state-of-the-art results on the same dataset, the prediction results demonstrate the superiority of the proposed network.

scholarly journals Time Interval to Biochemical Failure as a Surrogate End Point in Locally Advanced Prostate Cancer: Analysis of Randomized Trial NRG/RTOG 9202

2019 ◽  
Vol 37 (3) ◽  
pp. 213-221 ◽  
Author(s):  
James J. Dignam ◽  
Daniel A. Hamstra ◽  
Herbert Lepor ◽  
David Grignon ◽  
Harmar Brereton ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Randomized Trial ◽  
Locally Advanced ◽  
Biochemical Failure ◽  
Mediating Effect ◽  
Time Interval ◽  
Short Term ◽  
End Points ◽  
End Point

Background In prostate cancer, end points that reliably portend prognosis and treatment benefit (surrogate end points) can accelerate therapy development. Although surrogate end point candidates have been evaluated in the context of radiotherapy and short-term androgen deprivation (AD), potential surrogates under long-term (24 month) AD, a proven therapy in high-risk localized disease, have not been investigated. Materials and Methods In the NRG/RTOG 9202 randomized trial (N = 1,520) of short-term AD (4 months) versus long-term AD (LTAD; 28 months), the time interval free of biochemical failure (IBF) was evaluated in relation to clinical end points of prostate cancer–specific survival (PCSS) and overall survival (OS). Survival modeling and landmark analysis methods were applied to evaluate LTAD benefit on IBF and clinical end points, association between IBF and clinical end points, and the mediating effect of IBF on LTAD clinical end point benefits. Results LTAD was superior to short-term AD for both biochemical failure (BF) and the clinical end points. Men remaining free of BF for 3 years had relative risk reductions of 39% for OS and 73% for PCSS. Accounting for 3-year IBF status reduced the LTAD OS benefit from 12% (hazard ratio [HR], 0.88; 95% CI, 0.79 to 0.98) to 6% (HR, 0.94; 95% CI, 0.83 to 1.07). For PCSS, the LTAD benefit was reduced from 30% (HR, 0.70; 95% CI, 0.52 to 0.82) to 6% (HR, 0.94; 95% CI, 0.72 to 1.22). Among men with BF, by 3 years, 50% of subsequent deaths were attributed to prostate cancer, compared with 19% among men free of BF through 3 years. Conclusion The IBF satisfied surrogacy criteria and identified the benefit of LTAD on disease-specific survival and OS. The IBF may serve as a valid end point in clinical trials and may also aid in risk monitoring after initial treatment.

scholarly journals Long-Term Observations of Beach Variability at Hasaki, Japan

2020 ◽  
Vol 8 (11) ◽  
pp. 871
Author(s):  
Masayuki Banno ◽  
Satoshi Nakamura ◽  
Taichi Kosako ◽  
Yasuyuki Nakagawa ◽  
Shin-ichi Yanagishima ◽  
...  
Keyword(s):  
Morphological Change ◽  
High Frequency ◽  
Climate Changes ◽  
Wave Climate ◽  
Time Interval ◽  
Observation Data ◽  
Beach Profile ◽  
Water Level Variations ◽  
Monthly Variations

Long-term beach observation data for several decades are essential to validate beach morphodynamic models that are used to predict coastal responses to sea-level rise and wave climate changes. At the Hasaki coast, Japan, the beach profile has been measured for 34 years at a daily to weekly time interval. This beach morphological dataset is one of the longest and most high-frequency measurements of the beach morphological change worldwide. The profile data, with more than 6800 records, reflect short- to long-term beach morphological change, showing coastal dune development, foreshore morphological change and longshore bar movement. We investigated the temporal beach variability from the decadal and monthly variations in elevation. Extremely high waves and tidal anomalies from an extratropical cyclone caused a significant change in the long-term bar behavior and foreshore slope. The berm and bar variability were also affected by seasonal wave and water level variations. The variabilities identified here from the long-term observations contribute to our understanding of various coastal phenomena.

On-demand therapy with pantoprazole 20 mg as effective long-term managemnt of patients suffering from mild GERD

2003 ◽  
Vol 124 (4) ◽  
pp. A538 ◽  
Author(s):  
S. Kaspari ◽  
L. Kupcinskas ◽  
R. Fischer ◽  
P. Berghoefer
Keyword(s):  
On Demand

scholarly journals Application of the Monte Carlo Method for the Assessment of Long-term Success in Keratoprosthesis Surgery

2002 ◽  
Vol 4 (3) ◽  
pp. 183-190 ◽  
Author(s):  
W. Hitzl ◽  
G. Grabner
Keyword(s):  
Monte Carlo ◽  
Visual Acuity ◽  
Survival Analysis ◽  
Monte Carlo Method ◽  
Surgical Techniques ◽  
Distribution Functions ◽  
Time Interval ◽  
Specific Method ◽  
The Monte Carlo Method

The comparison of different methods of keratoprosthesis (KP) regarding their long-term success, as far as visual acuity is concerned, is difficult: this is the case both as a standardized reporting method agreed upon by all research groups has not been reported and far less accepted, and as the quality of life for the patient not only depends on the level of visual acuity, but also quite significantly on the “survival time” of the implant. Therefore, an analysis of a single series of patients with Osteo–Odonto–Keratoprosthesis (OOKP) was performed. Statistical analysis methods used by others in similar groups of surgical procedures have included descriptive statistics, survival analysis and ANOVA. These methods comprised comparisons of empirical densities or distribution functions and empirical survival curves. It is the objective of this paper to provide an inductive statistical method to avoid the problems with descriptive techniques and survival analysis. This statistical model meets four important standards: (1) the efficiency of a surgical technique can be assessed within an arbitrary time interval by a new index (VAT-index), (2) possible autocorrelations of the data are taken into consideration and (3) the efficiency is not only stated by a point estimator, but also 95% point-wise confidence limits are computed based on the Monte Carlo method, and finally, (4) the efficiency of a specific method is illustrated by line and range plots for quick illustration and can also be used for the comparison of different other surgical techniques such as refractive techniques, glaucoma and retinal surgery.

Long-Term Prospects of the International Wine Trade

2018 ◽  
Vol 13 (4) ◽  
pp. 442-450 ◽  
Author(s):  
Olivier Bargain ◽  
Jean-Marie Cardebat ◽  
Raphael Chiappini ◽  
Corentin Laffitte
Keyword(s):  
New Zealand ◽  
Great Emphasis ◽  
Market Structures ◽  
On Demand ◽  
The United Kingdom ◽  
Comparative Advantages ◽  
The Future ◽  
Jel Classifications ◽  
Wine Trade

AbstractThis article discusses key comparative advantages of wine-producing nations and suggest prospective views on their evolution. Our methodology is twofold. First, we study comparative advantages in 16 countries using Porter's diamond. Then, we report results from a survey in which wine economists are asked to assess the future trade performance of these countries. Results are relatively consistent across methods regarding the future “heavy weights” like China, but also New Zealand and Chile, countries show the greatest potential to succeed in the future global wine trade. It is also expected that Georgia, the United Kingdom, and Australia play an important role, although to a lesser extent. Our findings indicate that comparative advantages in wine trade are neither uniform nor static; especially, terroir is no longer sufficient. The diamond approach contradicts experts from two countries in particular, France and Argentina, suggesting that experts put great emphasis on demand and market structures as key trade determinants for the future. (JEL Classifications: F14, Q17)

scholarly journals Modelling tropical forest responses to drought and El Niño with a stomatal optimization model based on xylem hydraulics

2018 ◽  
Vol 373 (1760) ◽  
pp. 20170315 ◽  
Author(s):  
Cleiton B. Eller ◽  
Lucy Rowland ◽  
Rafael S. Oliveira ◽  
Paulo R. L. Bittencourt ◽  
Fernanda V. Barros ◽  
...  
Keyword(s):  
Tropical Forest ◽  
El Niño ◽  
Optimization Model ◽  
El Nino ◽  
Soil Drought ◽  
Forest Sites ◽  
Dynamic Global Vegetation Models ◽  
Vegetation Models ◽  
Global Vegetation

The current generation of dynamic global vegetation models (DGVMs) lacks a mechanistic representation of vegetation responses to soil drought, impairing their ability to accurately predict Earth system responses to future climate scenarios and climatic anomalies, such as El Niño events. We propose a simple numerical approach to model plant responses to drought coupling stomatal optimality theory and plant hydraulics that can be used in dynamic global vegetation models (DGVMs). The model is validated against stand-scale forest transpiration ( E ) observations from a long-term soil drought experiment and used to predict the response of three Amazonian forest sites to climatic anomalies during the twentieth century. We show that our stomatal optimization model produces realistic stomatal responses to environmental conditions and can accurately simulate how tropical forest E responds to seasonal, and even long-term soil drought. Our model predicts a stronger cumulative effect of climatic anomalies in Amazon forest sites exposed to soil drought during El Niño years than can be captured by alternative empirical drought representation schemes. The contrasting responses between our model and empirical drought factors highlight the utility of hydraulically-based stomatal optimization models to represent vegetation responses to drought and climatic anomalies in DGVMs. This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications’.

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