scholarly journals Data Files: Bi-objective Optimization for Battery Electric Bus Deployment Considering Cost and Environmental Equity

Author(s):  
Xiaoyue Liu ◽  
Yirong Zhou ◽  
Ran Wei ◽  
Aaron Golub
2021 ◽  
Author(s):  
Xiaoyue Liu ◽  
◽  
Yirong Zhou ◽  
Ran Wei ◽  
Aaron Golub ◽  
...  

Author(s):  
H. O. Colijn

Many labs today wish to transfer data between their EDS systems and their existing PCs and minicomputers. Our lab has implemented SpectraPlot, a low- cost PC-based system to allow offline examination and plotting of spectra. We adopted this system in order to make more efficient use of our microscopes and EDS consoles, to provide hardcopy output for an older EDS system, and to allow students to access their data after leaving the university.As shown in Fig. 1, we have three EDS systems (one of which is located in another building) which can store data on 8 inch RT-11 floppy disks. We transfer data from these systems to a DEC MINC computer using “SneakerNet”, which consists of putting on a pair of sneakers and running down the hall. We then use the Hermit file transfer program to download the data files with error checking from the MINC to the PC.


1998 ◽  
Vol 10 (1-3) ◽  
pp. 1-9
Author(s):  
Onno Boonstra ◽  
Maarten Panhuysen

Population registers are recognised to be a very important source for demographic research, because it enables us to study the lifecourse of individuals as well as households. A very good technique for lifecourse analysis is event history analysis. Unfortunately, there are marked differences in the way the data are available in population registers and the way event history analysis expects them to be. The source-oriented approach of computing historical data calls for a ‘five-file structure’, whereas event history analysis only can handle fiat files. In this article, we suggest a series of twelve steps with which population register data can be transposed from a five-file structured database into a ‘flat file’ event history analysis dataset.


Author(s):  
Umesh Banodha ◽  
Praveen Kumar Kataria

Cloud is an emerging technology that stores the necessary data and electronic form of data is produced in gigantic quantity. It is vital to maintain the efficacy of this data the need of data recovery services is highly essential. Cloud computing is anticipated as the vital foundation for the creation of IT enterprise and it is an impeccable solution to move databases and application software to big data centers where managing data and services is not completely reliable. Our focus will be on the cloud data storage security which is a vital feature when it comes to giving quality service. It should also be noted that cloud environment comprises of extremely dynamic and heterogeneous environment and because of high scale physical data and resources, the failure of data centre nodes is completely normal.Therefore, cloud environment needs effective adaptive management of data replication to handle the indispensable characteristic of the cloud environment. Disaster recovery using cloud resources is an attractive approach and data replication strategy which attentively helps to choose the data files for replication and the strategy proposed tells dynamically about the number of replicas and effective data nodes for replication. Thus, the objective of future algorithm is useful to help users together the information from a remote location where network connectivity is absent and secondly to recover files in case it gets deleted or wrecked because of any reason. Even, time oriented problems are getting resolved so in less time recovery process is executed.


2019 ◽  
Author(s):  
Federica Trudu ◽  
gloria tabacchi ◽  
Ettore Fois

1) main text file of the paper: "Computational modeling of open framework silicates: probing straight bond angles in ferrierite reveals intriguing links between mineralogy, nanomaterial science and technological applications"<div>by F. Trudu, G. Tabacchi, E. Fois (pdf file)</div><div>2) supporting information (pdf file)</div><div>3) zip folder containing relevant data files in cif format</div><div><br></div><div>Twitter handle of the submitting author:</div><div>@BL76276</div>


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