scholarly journals Evaluation of Community Livability Using Gridded Basic Urban Geographical Data—A Case Study of Wuhan

2022 ◽  
Vol 11 (1) ◽  
pp. 38
Author(s):  
Qiong Luo ◽  
Hong Shu ◽  
Zhongyuan Zhao ◽  
Rui Qi ◽  
Youxin Huang ◽  
...  

The evaluation of community livability quantifies the demands of human settlement at the micro scale, supporting urban governance decision-making at the macro scale. Big data generated by the urban management of government agencies can provide an accurate, real-time, and rich data set for livability evaluation. However, these data are intertwined by overlapping geographical management boundaries of different government agencies. It causes the difficulty of data integration and utilization when evaluating community livability. To address this problem, this paper proposes a scheme of partitioning basic geographical space into grids by optimally integrating various geographical management boundaries relevant to enterprise-level big data. Furthermore, the system of indexes on community livability is created, and the evaluation model of community livability is constructed. Taking Wuhan as an example, the effectiveness of the model is verified. After the evaluation, the experimental results show that the livability evaluation with reference to our basic geographic grids can effectively make use of governmental big data to spatially identify the multi-dimensional characteristics of a community, including management, environment, facility services, safety, and health. Our technical solution to evaluate community livability using gridded basic urban geographical data is of large potential in producing thematic data of community, constructing a 15-min community living circle of Wuhan, and enhancing the ability of the community to resist risks.

Author(s):  
Ângela Alpoim ◽  
Tiago Guimarães ◽  
Filipe Portela ◽  
Manuel Filipe Santos

2012 ◽  
Vol 72 (1) ◽  
pp. 134-167 ◽  
Author(s):  
SHEILAGH OGILVIE ◽  
MARKUS KÜPKER ◽  
JANINE MAEGRAITH

The “less-developed” interior of early modern Europe, especially the rural economy, is often regarded as financially comatose. This article investigates this view using a rich data set of marriage and death inventories for seventeenth-century Germany. It first analyzes the characteristics of debts, examining borrowing purposes, familial links, communal ties, and documentary instruments. It then explores how borrowing varied with gender, age, marital status, occupation, date, and asset portfolio. It finds that ordinary people, even in a “less-developed” economy in rural central Europe, sought to invest profitably, smooth consumption, bridge low liquidity, and hold savings in financial form.


Author(s):  
Yihao Tian

Big data is an unstructured data set with a considerable volume, coming from various sources such as the internet, business organizations, etc., in various formats. Predicting consumer behavior is a core responsibility for most dealers. Market research can show consumer intentions; it can be a big order for a best-designed research project to penetrate the veil, protecting real customer motivations from closer scrutiny. Customer behavior usually focuses on customer data mining, and each model is structured at one stage to answer one query. Customer behavior prediction is a complex and unpredictable challenge. In this paper, advanced mathematical and big data analytical (BDA) methods to predict customer behavior. Predictive behavior analytics can provide modern marketers with multiple insights to optimize efforts in their strategies. This model goes beyond analyzing historical evidence and making the most knowledgeable assumptions about what will happen in the future using mathematical. Because the method is complex, it is quite straightforward for most customers. As a result, most consumer behavior models, so many variables that produce predictions that are usually quite accurate using big data. This paper attempts to develop a model of association rule mining to predict customers’ behavior, improve accuracy, and derive major consumer data patterns. The finding recommended BDA method improves Big data analytics usability in the organization (98.2%), risk management ratio (96.2%), operational cost (97.1%), customer feedback ratio (98.5%), and demand prediction ratio (95.2%).


2021 ◽  
Author(s):  
◽  
Ellen Yarrow

<p>This study explores the relationship between professional contractors and the permanent employees they work with at organisations in New Zealand. This thesis uses two concepts, organisational socialisation and the psychological contract, as lenses through which the working relationship is explored. The 20th century notion of standard employment has largely been eroded, giving way to different forms of non-standard work. Professional contractors are now found performing a variety of roles in many organisations across this country. Many are doing the work of permanent employees, but they are neither employees nor permanent. Professional contractors are a type of non-standard, transient worker. As part of a blended workforce, professional contractors work alongside permanent employees, but little is known about how they work together.  This qualitative study involves 49 face-to-face interviews with professional contractors, permanent employees and managers working in the Information Technology (IT) divisions of 10 organisations in three major cities in New Zealand. This research design results in a rich data set. The data collected was subject to analysis using the software NVIVO. This data was analysed in relation to the literature on organisational socialisation and the psychological contract to further explain the working relationship between professional contractors and permanent employees.  The findings reveal professional contractors’ experience of Van Maanen’s (1979) socialisation tactics were: collective, informal, variable, random and serial. It was found that an organisation’s policy sets the tone for the treatment (induction, inclusion and management) of professional contractors. According to the professional contractors interviewed, the Chao, O'Leary-Kelly, Wolf, Klein, and Gardner (1994) socialisation content dimensions that are important are structure, culture and values and language but history was not considered important. According to the managers interviewed, contractors need to know about the processes and procedures of the client organisation, have strong technical skills and industry, sector or domain knowledge. It was found that the indicator of adjustment ‘acceptance by insiders’ (Bauer & Erdogan, 2012) may be a sign that the contractor is adjusting to their new role but it is not essential. A new indicator of adjustment for professional contractors – output – clearly emerged from the data. The notion of ‘time to productivity’ is highly relevant to professional contractors and three factors affecting it are identified (contractor capability, role complexity and organisation readiness). Another important finding is that permanent employees play a key role as socialisation agents (Feldman, 1994; Jones, 1983; Van Maanen, 1978) in the socialisation of professional contractors. Surprisingly, it was found that other professional contractors also act as socialisation agents assisting the newcomer to adjust. It was found that proactive socialisation is particularly important for professional contractors. Together these findings establish the need to reconceptualise organisational socialisation for professional contractors specifically.  The second part of this thesis explores the psychological contract by asking interviewees about their mutual expectations. The expectations of each of the three parties (managers, professional contractors, and permanent employees) are subtly different, potentially influencing the psychological contract they develop. Permanent employees expect great things, professionalism and independence from professional contractors. Managers expect speed, professionalism and value for money from contractors. On the other hand, professional contractors simply expect to be treated with respect by their colleagues. Professional contractors expect to be given autonomy by their managers and support or guidance, should they require it. This study was not able to ascertain what type of psychological contract a professional contractor may develop. It is possible that a professional contractor develops a hybrid psychological contract. Alternatively, it is possible that a professional contractor’s psychological contract moves between the types developed by Rousseau (1995) over the course of their term with the client organisation. The insights gained by exploring the expectations of professional contractors, permanent employees and their managers are two-fold. Firstly, these expectations provide a valuable insight into the working relationship. Secondly, the exploration of a breach or violation of the psychological contract indicates that a malleable psychological contract (one that will shift or adjust) is less likely to manifest a breach or violation. Therefore, it is better for a professional contractor to develop and maintain a malleable rather than rigid psychological contract.  This study’s findings highlight the interrelationship between organisational socialisation and the psychological contract. This thesis asserts that the working relationship between professional contractors and permanent employees is specifically influenced by the socialisation of contractors as newcomers and in the mutual expectations, which form the psychological contract. As a result, it contributes to theorising and understanding of the working relationship between professional contractors and permanent employees. It identifies several tensions in the co-dependent working relationship, which are: time, team, treatment and training. This study has implications for Human Resource practitioners and managers because there is a need for corporate or HR policy relating to the treatment professional contractors. The use of organisational socialisation and the psychological contract as lenses with which the working relationship is explored is both original and meaningful.</p>


2019 ◽  
Vol 2 ◽  
pp. 1-6
Author(s):  
Wenjuan Lu ◽  
Aiguo Liu ◽  
Chengcheng Zhang

<p><strong>Abstract.</strong> With the development of geographic information technology, the way to get geographical information is constantly, and the data of space-time is exploding, and more and more scholars have started to develop a field of data processing and space and time analysis. In this, the traditional data visualization technology is high in popularity and simple and easy to understand, through simple pie chart and histogram, which can reveal and analyze the characteristics of the data itself, but still cannot combine with the map better to display the hidden time and space information to exert its application value. How to fully explore the spatiotemporal information contained in massive data and accurately explore the spatial distribution and variation rules of geographical things and phenomena is a key research problem at present. Based on this, this paper designed and constructed a universal thematic data visual analysis system that supports the full functions of data warehousing, data management, data analysis and data visualization. In this paper, Weifang city is taken as the research area, starting from the aspects of rainfall interpolation analysis and population comprehensive analysis of Weifang, etc., the author realizes the fast and efficient display under the big data set, and fully displays the characteristics of spatial and temporal data through the visualization effect of thematic data. At the same time, Cassandra distributed database is adopted in this research, which can also store, manage and analyze big data. To a certain extent, it reduces the pressure of front-end map drawing, and has good query analysis efficiency and fast processing ability.</p>


A large volume of datasets is available in various fields that are stored to be somewhere which is called big data. Big Data healthcare has clinical data set of every patient records in huge amount and they are maintained by Electronic Health Records (EHR). More than 80 % of clinical data is the unstructured format and reposit in hundreds of forms. The challenges and demand for data storage, analysis is to handling large datasets in terms of efficiency and scalability. Hadoop Map reduces framework uses big data to store and operate any kinds of data speedily. It is not solely meant for storage system however conjointly a platform for information storage moreover as processing. It is scalable and fault-tolerant to the systems. Also, the prediction of the data sets is handled by machine learning algorithm. This work focuses on the Extreme Machine Learning algorithm (ELM) that can utilize the optimized way of finding a solution to find disease risk prediction by combining ELM with Cuckoo Search optimization-based Support Vector Machine (CS-SVM). The proposed work also considers the scalability and accuracy of big data models, thus the proposed algorithm greatly achieves the computing work and got good results in performance of both veracity and efficiency.


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