scholarly journals Designing a New Shuttle Service to Meet Large-Scale Instantaneous Peak Demands for Passenger Transportation in a Metropolitan Context: A Green, Low-Cost Mass Transport Option

2019 ◽  
Vol 11 (18) ◽  
pp. 5025 ◽  
Author(s):  
Zheng ◽  
Chen ◽  
Zhang ◽  
Yang
Keyword(s):  
Traffic Congestion ◽  
Large Scale ◽  
Clustering Algorithm ◽  
Low Cost ◽  
Routing Algorithm ◽  
Passenger Transportation ◽  
Rejection Mechanism ◽  
New Type ◽  
Hard Clustering ◽  
The Individual

Currently, the green, sustainable development of metropolises is hindered by problems caused by Large-scale Instantaneous Peak-demands for Passenger-transportation (LIPP), such as traffic congestion and air pollution. To mitigate these problems, we propose a new type of demand-responsive service as an alternative to inefficient “door-to-door” service. The proposed service is based on service units designed to aggregate passengers for shuttle service. To guarantee service quality and efficiency, a maximum passenger walking time constraint, a request rejection mechanism and a scheme for ensuring solution feasibility are considered. Through numerical experiments, we prove the following: (i) the proposed transport option exhibits better performance (by 40.37% for passengers and by 35.79% for operators) than the door-to-door transport option for solving real cases. (ii) By testing different datasets, we prove that the proposed service is more suitable for the request distributions that are spatiotemporally concentrated. (iii) Regarding the individual components of the proposed clustering-first, routing-second solution framework, the proposed soft clustering algorithm exhibits better performance than the classical hard clustering method (by 8%), and the proposed routing algorithm is 1.5 times more efficient than the commercial solution software GAMS.

scholarly journals Low-Cost IoT Remote Sensor Mesh for Large-Scale Orchard Monitorization

2020 ◽  
Vol 9 (3) ◽  
pp. 44
Author(s):  
Leonor Varandas ◽  
João Faria ◽  
Pedro Gaspar ◽  
Martim Aguiar
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Low Cost ◽  
Experimental Tests ◽  
Remote Measurement ◽  
Land Protection ◽  
Remote Monitoring System ◽  
Solar Powered ◽  
The Individual ◽  
System Nodes

Population growth and climate change lead agricultural cultures to face environmental degradation and rising of resistant diseases and pests. These conditions result in reduced product quality and increasing risk of harmful toxicity to human health. Thus, the prediction of the occurrence of diseases and pests and the consequent avoidance of the erroneous use of phytosanitary products will contribute to improving food quality and safety and environmental land protection. This study presents the design and construction of a low-cost IoT sensor mesh that enables the remote measurement of parameters of large-scale orchards. The developed remote monitoring system transmits all monitored data to a central node via LoRaWAN technology. To make the system nodes fully autonomous, the individual nodes were designed to be solar-powered and to require low energy consumption. To improve the user experience, a web interface and a mobile application were developed, which allow the monitored information to be viewed in real-time. Several experimental tests were performed in an olive orchard under different environmental conditions. The results indicate an adequate precision and reliability of the system and show that the system is fully adequate to be placed in remote orchards located at a considerable distance from networks, being able to provide real-time parameters monitoring of both tree and the surrounding environment.

scholarly journals Integrated bioprocess for conversion of gaseous substrates to liquids

2016 ◽  
Vol 113 (14) ◽  
pp. 3773-3778 ◽  
Author(s):  
Peng Hu ◽  
Sagar Chakraborty ◽  
Amit Kumar ◽  
Benjamin Woolston ◽  
Hongjuan Liu ◽  
...  
Keyword(s):  
Acetic Acid ◽  
Synthesis Gas ◽  
Large Scale ◽  
Low Cost ◽  
Cost Effective ◽  
Integrated System ◽  
Biodiesel Production ◽  
Liquid Fuels ◽  
Acid Product ◽  
The Individual

In the quest for inexpensive feedstocks for the cost-effective production of liquid fuels, we have examined gaseous substrates that could be made available at low cost and sufficiently large scale for industrial fuel production. Here we introduce a new bioconversion scheme that effectively converts syngas, generated from gasification of coal, natural gas, or biomass, into lipids that can be used for biodiesel production. We present an integrated conversion method comprising a two-stage system. In the first stage, an anaerobic bioreactor converts mixtures of gases of CO2 and CO or H2 to acetic acid, using the anaerobic acetogen Moorella thermoacetica. The acetic acid product is fed as a substrate to a second bioreactor, where it is converted aerobically into lipids by an engineered oleaginous yeast, Yarrowia lipolytica. We first describe the process carried out in each reactor and then present an integrated system that produces microbial oil, using synthesis gas as input. The integrated continuous bench-scale reactor system produced 18 g/L of C16-C18 triacylglycerides directly from synthesis gas, with an overall productivity of 0.19 g⋅L−1⋅h−1 and a lipid content of 36%. Although suboptimal relative to the performance of the individual reactor components, the presented integrated system demonstrates the feasibility of substantial net fixation of carbon dioxide and conversion of gaseous feedstocks to lipids for biodiesel production. The system can be further optimized to approach the performance of its individual units so that it can be used for the economical conversion of waste gases from steel mills to valuable liquid fuels for transportation.

Appropriate technologies for the future

1980 ◽  
Vol 209 (1174) ◽  
pp. 183-186 ◽  
Keyword(s):  
Food Production ◽  
Large Scale ◽  
Low Cost ◽  
Health Needs ◽  
Small Scale ◽  
Cost Of Energy ◽  
Prophylactic Measures ◽  
The Future ◽  
The Individual ◽  
The Third World

Crystal ball gazing is a hazardous occupation: the sharper the picture, the greater the possibility of error. In the future, appropriate technologies that will raise standards of health and diminish the prevalence of disease in the Third World must take cognizance of such factors as burgeoning population growth, impossibly high cost of energy sources, a widening gap between food requirements and food production, increasing urbanization, and inherent difficulties of control of disease vectors and water-borne diseases. The technologies that must be made available will be both large-scale and small-scale, low-cost and simple, improving life for the individual and the community, mediated by appropriately trained and adequately supervised polycompetent auxiliaries. The present reappraisal of health needs in the context of food (seeds, soils, irrigation, protection against loss of the harvested products) and of prevention of disease by appropriate prophylactic measures and its treatment, will necessitate hard thinking and greater cooperation between all concerned.

A Novel Manufacturing Chain for Low Cost 3D Textile Reinforced Polymer Composites

2014 ◽  
Vol 980 ◽  
pp. 230-234
Author(s):  
Ana Almansa ◽  
Monireh Fazeli ◽  
Benoit Laurent ◽  
Pere Padros ◽  
Marianne Hörlesberger
Keyword(s):  
Flexible Manufacturing ◽  
Large Scale ◽  
Low Cost ◽  
Composite Part ◽  
Hybrid Yarn ◽  
Reinforced Polymer ◽  
Novel Approach ◽  
End Products ◽  
The Individual ◽  
Manufacturing Chain

The project 3D-LightTrans aims to create a highly flexible manufacturing chain for the low cost production of integral large scale 3D textile reinforced polymer composite parts. In a novel approach, multi-material semi-finished fabrics made of hybrid yarn are formed to deep draped pre-fixed multi-layered and multifunctional 3D-textile pre-forms. These are then efficiently processed into the final composite part by thermoforming. This paper presents the results achieved by the project consortium during the last three years, including the development and optimization of the individual processes for prototype production, with a focus on two selected automotive end products, and the adaption of equipment for industrial scale manufacturing.

Study on the Properties of Spherical Pore Porous Metal Prepared by Plastic Working

2011 ◽  
Vol 80-81 ◽  
pp. 128-132
Author(s):  
Li Zhong Zhang ◽  
Guo Dong Shi ◽  
Lin Lin Xu ◽  
Yong Jiang Yu ◽  
Xiao Jun Zhao
Keyword(s):  
Large Scale ◽  
Low Cost ◽  
Porous Metal ◽  
Metal Structure ◽  
Metal Plate ◽  
The Body ◽  
Main Body ◽  
Porous Metals ◽  
High Productivity ◽  
New Type

This paper reveals a preparation method of a new type of porous metal. Because of the high cost and low quality, the actual large-scale application of porous metal is not very widespread. The new manufacturing methods proposed by paper will enhance the practical application of porous metals. The hollow part of hollow metal balls can be used as the main body of porous metal to manufacture porous metal. First, a hemispherical-thin layer metal structure was obtained by plastic processing from a metal plate. Then, this metal structure was connected appropriately according to the body-centered cubic structure to from a new type of spherical porous metal. The method is simple, high productivity, easy control and low cost.

scholarly journals Fuzzy Weight Cluster-Based Routing Algorithm for Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-12
Author(s):  
Teng Gao ◽  
Jin-Yan Song ◽  
Jin-Hua Ding ◽  
De-Quan Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Large Scale ◽  
Clustering Algorithm ◽  
Direct Method ◽  
Routing Algorithm ◽  
Wireless Sensor ◽  
Aggregated Data ◽  
Cluster Heads ◽  
Engineering Theory

Cluster-based protocol is a kind of important routing in wireless sensor networks. However, due to the uneven distribution of cluster heads in classical clustering algorithm, some nodes may run out of energy too early, which is not suitable for large-scale wireless sensor networks. In this paper, a distributed clustering algorithm based on fuzzy weighted attributes is put forward to ensure both energy efficiency and extensibility. On the premise of a comprehensive consideration of all attributes, the corresponding weight of each parameter is assigned by using the direct method of fuzzy engineering theory. Then, each node works out property value. These property values will be mapped to the time axis and be triggered by a timer to broadcast cluster headers. At the same time, the radio coverage method is adopted, in order to avoid collisions and to ensure the symmetrical distribution of cluster heads. The aggregated data are forwarded to the sink node in the form of multihop. The simulation results demonstrate that clustering algorithm based on fuzzy weighted attributes has a longer life expectancy and better extensibility than LEACH-like algorithms.

scholarly journals Scarf: A toolkit for memory efficient analysis of large-scale single-cell genomics data

2021 ◽  
Author(s):  
Parashar Dhapola ◽  
Johan Rodhe ◽  
Rasmus Olofzon ◽  
Thomas Bonald ◽  
Eva Erlandsson ◽  
...  
Keyword(s):  
Single Cell ◽  
Large Scale ◽  
Clustering Algorithm ◽  
Single Cell Analysis ◽  
Low Cost ◽  
Rna Seq ◽  
Representative Sampling ◽  
Lineage Differentiation ◽  
Memory Efficiency ◽  
Memory Efficient

The increasing capacity to perform large-scale single-cell genomic experiments continues to outpace the ability to efficiently handle growing datasets. Herein we present Scarf, a modularly designed Python package that seamlessly interoperates with other single-cell toolkits and allows for memory efficient single-cell analysis of millions of cells on a laptop or low-cost devices like single board computers. We demonstrate Scarf's memory and compute-time efficiency by applying it to the largest existing single-cell RNA-Seq and ATAC-Seq datasets. Scarf wraps memory efficient implementations of a graph-based t-stochastic neighbour embedding and hierarchical clustering algorithm. Moreover, Scarf performs accurate reference-anchored mapping of datasets while maintaining memory efficiency. By implementing a novel data downsampling algorithm, Scarf additionally has the capacity to generate representative sampling of cells from a given dataset wherein rare cell populations and lineage differentiation trajectories are conserved. Together, Scarf provides a framework wherein any researcher can perform advanced processing, downsampling, reanalysis and integration of atlas-scale datasets on standard laptop computers.

scholarly journals The analysis of urban taxi carpooling impact from taxi GPS data

2018 ◽  
Vol 47 (3) ◽  
pp. 109-120 ◽  
Author(s):  
Qiang Xiao ◽  
Ruichun He ◽  
Changxi Ma
Keyword(s):  
Traffic Congestion ◽  
Clustering Algorithm ◽  
Hot Spot ◽  
Probability Model ◽  
Central City ◽  
Gps Data ◽  
Effective Implementation ◽  
Passenger Transportation ◽  
Trip Time ◽  
Trip Distance

Taxi is an important part of urban passenger transportation system. The research and analysis of taxi trip behavior is the key to meet the demand of urban passenger transport and solve the traffic congestion problem. Based on the GPS data of taxis in Nanjing, the statistical method is used to analyze the taxi characteristics of the average number of passengers, the average passenger time, the no-load distance and the passenger distance. By using the double logarithmic coordinate, the trip distance and trip time of taxi passengers are analyzed, it is found that the average trip distance of taxi passengers is mainly concentrated in 3-20km, and the average trip time of taxi passengers is mainly concentrated in 10-30 minutes. Using the information entropy theory to construct the equilibrium model of taxi passenger-carrying point, and analyze the spatial distribution of taxi, it is found that the distribution of urban taxi is unbalanced. The peak clustering algorithm is used to determine the location of passenger gathering points, and the hot spot of taxi trip is analyzed, it is found that the hot spots of taxi trip are mainly concentrated in the central city of Nanjing. Combined with the results of urban taxi trip analysis, from the perspective of taxi and passenger, we found that the number of urban taxis, the passenger carrying rate of taxis, the duration period of passenger trip, the duration and distance of passenger trip and the location of passenger trip points will have an impact on the urban taxi carpooling in Nanjing. By using the probability model of urban taxi carpooling, this paper discusses and analyzes the influence of these factors on urban taxi carpooling. The research in this paper can provide a reference for the effective implementation of urban taxi carpooling policy.

Fast graph clustering in large-scale systems based on spectral coarsening

2021 ◽  
pp. 2150131
Author(s):  
Dasong Sun
Keyword(s):  
Complex Networks ◽  
Large Scale ◽  
Clustering Algorithm ◽  
Graph Clustering ◽  
Superior Performance ◽  
Computational Time ◽  
Single Node ◽  
Multiple Datasets ◽  
Spectral Algorithm ◽  
The Individual

Complex networks depict the individual relationship in a population, which can help to deeply mine the characteristics of complex networks and predict the potential collaboration between individuals by analyzing their interaction within different groups or clusters. However, the existing algorithms are with high complexity, which cost much computational time. In this paper, an efficient graph clustering algorithm based on spectral coarsening is proposed, to deal with the large time complexity of the traditional spectral algorithm. We first find the subset most possibly belonged to the same cluster in the original network, and merge them into a single node. The scale of the network will decrease with the network being coarsened. Then, the spectral clustering algorithm is performed on the coarsened network with the maintained advantages and the improved time efficiency. Finally, the experimental results on the multiple datasets demonstrate that the proposed algorithm, compared with the current state-of-the-art methods, has superior performance.

scholarly journals Automated protein crystal optimisation with TTP Labtech's dragonfly

2014 ◽  
Vol 70 (a1) ◽  
pp. C1743-C1743
Author(s):  
Joby Jenkins ◽  
Gary Cochrane
Keyword(s):  
Large Scale ◽  
Low Cost ◽  
Protein Crystal ◽  
X Ray Diffraction ◽  
High Resolution Structure ◽  
Crystallization Conditions ◽  
Screening Assays ◽  
Set Up ◽  
The Individual

The ability to crystallise proteins, nucleic acids or macromolecular complexes pose significant challenges to the protein crystallography community, from large scale screening assays for the determination of initial crystallization conditions, screen optimisation and final screen set-up. Protein crystal optimisation is vital to ensure high quality X ray diffraction data for the solving of high resolution structure. This process involves the set-up of a series of complex screening combinations where the ratios of the individual components identified from primary crystallisation studies are varied. In order to reduce the effort and tedium of this process, TTP Labtech have introduced dragonfly as an addition to their successful mosquito liquid handling portfolio for crystallisation screening. This poster demonstrates that "dragonfly" is a valuable, compact, low cost addition to the crystallographer's bench. It eliminates lengthy and complicated plate set-up at the optimisation stage of crystallisation.

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