scholarly journals Analysis and optimization of 15-minute community life circle based on supply and demand matching: A case study of Shanghai

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256904
Author(s):  
Haoyuan Wu ◽  
Liangxu Wang ◽  
Zhonghao Zhang ◽  
Jun Gao
Keyword(s):  
Supply And Demand ◽  
Living Environment ◽  
Community Life ◽  
Data Set ◽  
Basic Service ◽  
Downtown Area ◽  
Service Convenience ◽  
Comprehensive Service ◽  
Different Types ◽  
Life Circle

The 15-minute community life circle (15min-CLC) strategy is one of Shanghai’s important methods for building a global city and facing a society with a more diverse population structure in the future. In the existing research, the balance between the construction of the life circle and the needs of the people in the life circle still needs to be further fulfilled. This paper is based on the city’s multi-source large data set including 2018 AutoNavi POI (Point of Interests), OSM (OpenStreetMap) road network data and LandScan population data set, and evaluates the current status of Shanghai’s 15min-CLC through the fusion of kernel density estimation, service area analysis and other statistical models and proposes relevant optimization suggestions. The results show that there are the following shortcomings: (1) From the perspective of different types of infrastructure service facilities, the spatial construction of Shanghai’s overall life service facilities and shopping service facilities needs to be optimized. (2) From the perspective of comprehensive evaluation, the comprehensive service convenience of infrastructure service facilities in the downtown area is relatively high, while the comprehensive service convenience of urban infrastructure service facilities in the suburbs and outer suburbs is relatively low; The diversity of basic service facilities in the 15min-CLC in the downtown area is more consistent with the population distribution; However, in the peripheral areas of the urban area, too many infrastructure service facilities have been constructed. Based on the above shortcomings and the perspective of supply and demand matching, relevant optimization strategies are proposed in different regions and different types of infrastructure service facilities: (1) focus on the construction of basic service facilities in the urban fringe and urban-rural areas, improve the full coverage of the basic service facilities, and appropriately reduce the number of basic service facilities in the downtown area. (2) The development of community business models can be used to promote the development of new life service facilities and shopping service facilities. (3) Improve community medical institutions through facility function conversion, merger and reconstruction, etc. (4) Optimize the hierarchical basic service facility system and improve the population supporting facilities of basic service facilities in the 15min-CLC. This paper incorporates people’s needs and concerns on the living environment into the 15min-CLC evaluation model, and uses Shanghai as an example to conduct research, summarizes the existing shortcomings, and proposes corresponding optimization strategies based on the matching of supply and demand. This article attempts to explore a replicable 15min-CLC planning model, so that it can be extended to the Yangtze River Delta urban agglomeration, to provide reference for further research on the 15min-CLC, and to promote urban construction under the concept of sustainable development.

Comparative Analysis of Machine Learning Techniques Using Predictive Modeling

2020 ◽  
Vol 13 ◽  
Author(s):  
Ritu Khandelwal ◽  
Hemlata Goyal ◽  
Rajveer Singh Shekhawat
Keyword(s):  
Machine Learning ◽  
Comparative Analysis ◽  
Data Science ◽  
Training Data ◽  
Machine Learning Techniques ◽  
Future Trends ◽  
Data Set ◽  
Learning Stage ◽  
Learning Techniques ◽  
Different Types

Introduction: Machine learning is an intelligent technology that works as a bridge between businesses and data science. With the involvement of data science, the business goal focuses on findings to get valuable insights on available data. The large part of Indian Cinema is Bollywood which is a multi-million dollar industry. This paper attempts to predict whether the upcoming Bollywood Movie would be Blockbuster, Superhit, Hit, Average or Flop. For this Machine Learning techniques (classification and prediction) will be applied. To make classifier or prediction model first step is the learning stage in which we need to give the training data set to train the model by applying some technique or algorithm and after that different rules are generated which helps to make a model and predict future trends in different types of organizations. Methods: All the techniques related to classification and Prediction such as Support Vector Machine(SVM), Random Forest, Decision Tree, Naïve Bayes, Logistic Regression, Adaboost, and KNN will be applied and try to find out efficient and effective results. All these functionalities can be applied with GUI Based workflows available with various categories such as data, Visualize, Model, and Evaluate. Result: To make classifier or prediction model first step is learning stage in which we need to give the training data set to train the model by applying some technique or algorithm and after that different rules are generated which helps to make a model and predict future trends in different types of organizations Conclusion: This paper focuses on Comparative Analysis that would be performed based on different parameters such as Accuracy, Confusion Matrix to identify the best possible model for predicting the movie Success. By using Advertisement Propaganda, they can plan for the best time to release the movie according to the predicted success rate to gain higher benefits. Discussion: Data Mining is the process of discovering different patterns from large data sets and from that various relationships are also discovered to solve various problems that come in business and helps to predict the forthcoming trends. This Prediction can help Production Houses for Advertisement Propaganda and also they can plan their costs and by assuring these factors they can make the movie more profitable.

scholarly journals Field-based investigation of aged biochar coupled with summer legumes effect on wheat yield in Pakistan

2020 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Hafeez Ur Rahim ◽  
Sajjad Ahmad ◽  
Zaid Khan ◽  
Muhammad Ayoub Khan
Keyword(s):  
Maximum Yield ◽  
Wheat Yield ◽  
Wheat Crop ◽  
Human Consumption ◽  
Thousand Grain Weight ◽  
Data Set ◽  
Different Types ◽  
Biological Yield ◽  
Soil Fertility Improvement

There is a debate about whether the aged biochar effect can increase the crop yield or not. Herein, a field-based experimental data set and analysis provide the information on the aged biochar effect coupled with summer legumes on the yield of subsequent wheat. Briefly, in summer 2016, three different types of legumes i.e. mungbean, sesbania, and cowpea were grown with the intention of grain for human consumption, green manuring for soil fertility improvement, and fodder for livestock consumption. A fallow was also adjusted in the experiment with the purpose of comparison. Biochar was added to each experimental plot in triplicates at the rate of 0, 5, and 10 tons ha-1. After the harvesting of legumes, the biomass of each sesbania treatment plot was mixed in the field while the biomass of mungbean and cowpea were removed from each respective plot. To investigate the aged biochar effect, the wheat crop was grown on the same field layout and design (randomized complete block) of legumes. The data analysis highlighted that significantly maximum grain yield (kg ha-1), biological yield (kg ha-1); thousand-grain weight (g), and straw yield (kg ha-1) were obtained in the plots mixed with sesbania. Regarding the aged biochar effect, maximum yield was obtained in the plots with 10 tons ha-1treatment dose. Additionally, the interaction of aged biochar coupled with legumes was non-significant. In conclusion, this work could prove that aged biochar coupled with summer legumes enhanced the yield of subsequent wheat on a sustainable basis due to its long-term numerous benefits to the soil-plant system.

Too tied to fail: a multidimensional approach to social capital in crowdfunding campaigns. Evidences from Italian agri-food businesses

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ulpiana Kocollari ◽  
Alessia Pedrazzoli ◽  
Maddalena Cavicchioli ◽  
Andrea Girardi
Keyword(s):  
Social Capital ◽  
Design Methodology ◽  
Multidimensional Approach ◽  
Data Set ◽  
Content Type ◽  
Different Types ◽  
Linear Regressions ◽  
Practical Implications

PurposeThe authors investigate the contributions of social capital (SC) dimensions (bridging, bonding and linking) in crowdfunding campaigns by comparing the dynamics of agri-food businesses with those of two other sectors – cultural and technological.Design/methodology/approachThe authors develop linear regressions on a proprietary data set of 5,290 projects launched on the Italian platform “Produzionidalbasso.com”, from 2014 to 2020.FindingsThe authors’ findings suggest that combining the three social capital dimensions (bridging, bonding and linking) has a more substantial overall effect on the number of backers involved in agri-food projects than in cultural and technological projects. Agri-food entrepreneurs effectively mobilize all resources embedded in the SC dimensions and therefore create the conditions to develop new ties that financially support the project.Practical implicationsAgri-food entrepreneurs may benefit from those results improving their funding strategies. Therefore, agri-food entrepreneurs can explore and exploit the instruments available on the CFD platform – video and rewards associated with the campaign – gaining more benefit from the backers involved compared with other project categories.Originality/valueThe study proposes a broader perspective regarding SC that encompasses the proponent, the company and the campaign with three different types of ties: bonding, bridging and linking. These SC dimensions can differently shape diverse sectors and this eclectic configuration can differentiate the effects of SC in crowdfunding campaigns. This study pinpoints how crowdfunding determinants change, based on project categories.

Modeling Bus Travel Time Reliability with Supply and Demand Data from Automatic Vehicle Location and Smart Card Systems

2015 ◽  
Vol 2533 (1) ◽  
pp. 17-27 ◽  
Author(s):  
Zhen-Liang Ma ◽  
Luis Ferreira ◽  
Mahmoud Mesbah ◽  
Ahmad Tavassoli Hojati
Keyword(s):  
Travel Time ◽  
Smart Card ◽  
Supply And Demand ◽  
Seemingly Unrelated Regression ◽  
Regression Equations ◽  
Travel Time Reliability ◽  
Automatic Vehicle Location ◽  
Different Types ◽  
Vehicle Location ◽  
Bus Travel Time

Travel time reliability is an important aspect of bus service quality. Despite a significant body of research on private vehicle reliability, little attention has been paid to bus travel time reliability at the stop-to-stop link level on different types of roads. This study aims to identify and quantify the underlying determinants of bus travel time reliability on links of different road types with the use of supply and demand data from automatic vehicle location and smart card systems collected in Brisbane, Australia. Three general bus-related models were developed with respect to the main concerns of travelers and planners: average travel time, buffer time, and coefficient of variation of travel time. Five groups of alternative models were developed to account for variations caused by different road types, including arterial road, motorway, busway, and central business district. Seemingly unrelated regression equations estimation were applied to account for cross-equation correlations across regression models in each group. Three main categories of unreliability contributory factors were identified and tested in this study, namely, planning, operational, and environmental. Model results provided insights into these factors that affect bus travel time and its variability. The most important predictors were found to be the recurrent congestion index, traffic signals, and passenger demand at stops. Results could be used to target specific strategies aimed at reducing unreliability on different types of roads.

Correlation guided Network Integration (CoNI) reveals novel genetic regulators of hepatic metabolism

2020 ◽  
Author(s):  
Valentina S. Klaus ◽  
Sonja C. Schriever ◽  
Andreas Peter ◽  
José Manuel Monroy Kuhn ◽  
Martin Irmler ◽  
...  
Keyword(s):  
Ex Vivo ◽  
Hepatic Metabolism ◽  
Omics Data ◽  
Network Integration ◽  
Data Set ◽  
Metabolomics Data ◽  
Different Types ◽  
Hepatic Fat ◽  
Liver Biopsies

ABSTRACTThe steadily increasing amount of newly generated omics data of various types from genomics to metabolomics is a chance and a challenge to systems biology. To fully use its potential, one key is the meaningful integration of different types of omics. We here present a fully unsupervised and versatile correlation-based method, termed Correlation guided Network Integration (CoNI), to integrate multi-omics data into a hypergraph structure that allows for identification of effective regulators. Our approach further unravels single transcripts mapped to specific densely connected metabolic sub-graphs or pathways. By applying our method on transcriptomics and metabolomics data from murine livers under standard chow or high-fat-diet, we isolated eleven genes with a regulatory effect on hepatic metabolism. Subsequent in vitro and ex vivo experiments in human liver cells and human obtained liver biopsies validated seven candidates including INHBE and COBLL1, to alter lipid metabolism and to correlate with diabetes related traits such as overweight, hepatic fat content and insulin resistance (HOMA-IR). Last, we successfully applied our methods to an independent data-set to confirm its versatile and transferable character.

scholarly journals Harmonic Analysis via an Integral Equation: An Application to Dengue Transmission

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
R. G. U. I. Meththananda ◽  
N. C. Ganegoda ◽  
S. S. N. Perera
Keyword(s):  
Integral Equation ◽  
Parameter Estimation ◽  
Harmonic Analysis ◽  
Basis Functions ◽  
Periodic Waves ◽  
Data Set ◽  
New Approach ◽  
Dengue Transmission ◽  
Different Types ◽  
The Laplace Transform

A collection of oscillatory basis functions generated via an integral equation is investigated here. This is a new approach in the harmonic analysis as we are able to interpret phenomena with damping and amplifying oscillations other than classical Fourier-like periodic waves. The proposed technique is tested with a data set of dengue incidence, where different types of influences prevail. An intermediate transform supported by the Laplace transform is available. It facilitates parameter estimation and strengthens the extraction of hidden influencing accumulations. This mechanistic work can be extended as a tool in signal processing that encounters oscillatory and accumulated effects.

A Social-Aware Service Recommendation Approach for Mashup Creation

2013 ◽  
Vol 10 (1) ◽  
pp. 53-72 ◽  
Author(s):  
Jian Cao ◽  
Wenxing Xu ◽  
Liang Hu ◽  
Jie Wang ◽  
Minglu Li
Keyword(s):  
Social Relationships ◽  
State Of The Art ◽  
Value Added ◽  
The Internet ◽  
Service Recommendation ◽  
Data Set ◽  
Factorization Algorithm ◽  
Comprehensive Service ◽  
Daunting Task ◽  
User Centric

Mashup is a user-centric approach to create value-added new services by utilizing and recombining existing service components. However, as services become increasingly more spontaneous and prevalent on the Internet, finding suitable services from which to develop a mashup based on users’ explicit and implicit requirements remains a daunting task. Several approaches already exist for recommending specific services for users but they are limited to proposing only services with similar functionality. In order to recommend a set of suitable services for a general mashup based on users’ functional specifications, a novel social-aware service recommendation approach, where multi-dimensional social relationships among potential users, topics, mashups, and services are described by a coupled matrices model, is proposed in this paper. Accordingly, a factorization algorithm is designed to predict unobserved relationships, and we use a genetic algorithm to learn some specific parameters, and then construct a comprehensive service recommendation model. Experimental results for a realistic mashup data set indicate that the proposed approach outperforms other state-of-the-art methods.

Disaggregate Economic Base Multipliers in Small Communities

1997 ◽  
Vol 29 (6) ◽  
pp. 955-974 ◽  
Author(s):  
A C Vias ◽  
G F Mulligan
Keyword(s):  
Economic Base ◽  
Input Output ◽  
Data Set ◽  
Small Communities ◽  
Considerable Evidence ◽  
Transfer Payments ◽  
New Models ◽  
Base Analysis ◽  
Different Types ◽  
Community Data

Economic base analysis is frequently used to describe employment profiles and to predict project-related impacts in small communities. Considerable evidence suggests, however, that economic base multipliers should be estimated from survey data and not from shortcut methods. In this paper two competing versions of the economic base model are developed and then these two models are estimated by use of the Arizona community data set. In both cases, marginal multiplier estimates, controlled for transfer payments, are generated for ten individual sectors in five different types of communities. Results from these two disaggregate economic base models are assessed and then compared with results provided earlier by more aggregate models. The better of these two new models closely resembles the popular input—output model.

Delineation of Blood Vessels in Coronary Artery Region for Classification of Different Types of Plaques

2020 ◽  
Vol 10 (7) ◽  
pp. 901-914
Author(s):  
D. Indumathy ◽  
S. Sudha
Keyword(s):  
Cardiovascular Diseases ◽  
Blood Vessel ◽  
Heart Defects ◽  
Image Data ◽  
Data Set ◽  
Different Types ◽  
Cardiac Muscles ◽  
Pixel Analysis ◽  
Effective Medication

Cardiac arrest in human arises owing to blood vessel diseases or heart defects. Blood vessel diseases result due to the blockage of blood in the heart vessels, which leads to pain in the heart. Heart defects occur because of damage in the cardiac muscles indicated by abnormal heart rhythms. Cardiovascular diseases cause mortality which could be avoided through the earlier detection of cardiovascular diseases. The major cause for cardiovascular diseases is cholesterol deposition inside the artery walls which later forms plaques that block the blood flow. Until now, plaques have been detected through medical imaging only after the heart attack. The plaques are blasted through angioplasty or reduced with medicine. Classification of the plaques before treatment, leads to effective medication based on the type of plaque. The sub classification of the plaque types such as rupture-prone plaque, ruptured plaque with sub occlusive thrombus, erosion-prone plaque, calcified nodule and non-plaque has been segmented and identified. In this paper, we propose a novel Spatial Fuzzy Propensity Score Matching (SFPSM) method to classify the plaques. The SFPSM method consists of clustering, ranking the cluster and region-based pixel wise analysis. Pixel analysis inspects specific regions of sub pixel points and calibrates the plaque. From the experimental results, the classification of plaque based on the 50-image data set has exhibited accuracy of 85% after validation. The plaque accuracy of classification provides the standard digital number values for the sub classification of plaques.

Linking supplier selection and management strategies with mass customization capability

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Inayat Ullah ◽  
Rakesh Narain
Keyword(s):  
Mass Customization ◽  
Supplier Selection ◽  
Management Strategies ◽  
Supplier Management ◽  
Data Set ◽  
Content Type ◽  
Selection Strategies ◽  
Manufacturing Organizations ◽  
Different Types ◽  
Practical Implications

Purpose Owing to the paucity of literature, in the specific context of mass customization (MC), that explains what factors need to be considered while selecting suppliers and what strategies need to be implemented for effective management of suppliers, this paper aims to explore the effective supplier selection and management strategies and also investigate their impact on the development of mass customization capability (MCC). Design/methodology/approach Through an extensive review of literature, a total of 18 factors for supplier selection and management have been identified. Further, using multiple regression analysis, the linkages between these factors and MCCs have been examined based on the data set from the survey of Indian manufacturing organizations. Findings The results indicate that while concentrating on the responsive and reconfiguration capability, all the five measures of supplier selection and the four measures of supplier management have shown a significant influence. However, in the case of relational capability, only two of the supplier selection strategies and three of the supplier management strategies have shown a notable impact. Practical implications The study provides help to the firms in deciding whom to select and how to manage the suppliers in the course of improving their MCCs. The study has shown the possibility that different types of MCCs might require different approaches to both the supplier selection and management. Originality/value To the best of the authors’ knowledge, this study happens to be the first of its kind that investigates the interconnectedness among the supplier selection and management strategies and MCCs.

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