scholarly journals Data Management Model Selection: IT Professionals’ Preferences

2015 ◽  
Author(s):  
Gholam Shaykhian ◽  
Mohd Khairi ◽  
Jinan Ziade
2012 ◽  
pp. 1007-1022
Author(s):  
Konstantinos C. Zapounidis ◽  
Glykeria Kalfakakou

This paper’s aim is to analyse practices adapted by different enterprises regarding personnel motivation and human resources approaches to increase their productivity and profitability while examining the methodology of human resources recruitment and selection used by different kinds of enterprises, which cannot exist without human manpower. The objective of this paper is to analyse methods and tools used by several enterprises in motivation and in human resources recruitment and selection. Regarding motivation, the basic aim of the process adapted was to define whether each enterprise was closer to the participating or to directive management model. Especially in the recruiting and selecting process IT could add important value since adapted IT processes could lead to quicker and more successful transparent results. IT professionals could organise these processes for every enterprise in order to become standard, formulated, and even more accredited procedures which would lead to successful recruiting and selecting results.


2016 ◽  
pp. 1205-1222
Author(s):  
Mohammed A. AlZain ◽  
Alice S. Li ◽  
Ben Soh ◽  
Eric Pardede

Cloud computing is a phenomenal distributed computing paradigm that provides flexible, low-cost on-demand data management to businesses. However, this so-called outsourcing of computing resources causes business data security and privacy concerns. Although various methods have been proposed to deal with these concerns, none of these relates to multi-clouds. This paper presents a practical data management model in a public and private multi-cloud environment. The proposed model BFT-MCDB incorporates Shamir's Secret Sharing approach and Quantum Byzantine Agreement protocol to improve trustworthiness and security of business data storage, without compromising performance. The performance evaluation is carried out using a cloud computing simulator called CloudSim. The experimental results show significantly better performance in terms of data storage and data retrieval compared to other common cloud cryptographic based models. The performance evaluation based on CloudSim experiments demonstrates the feasibility of the proposed multi-cloud data management model.


Geosciences ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 25 ◽  
Author(s):  
Lifeng Yuan ◽  
Tadesse Sinshaw ◽  
Kenneth J. Forshay

Watershed-scale nonpoint source (NPS) pollution models have become important tools to understand, evaluate, and predict the negative impacts of NPS pollution on water quality. Today, there are many NPS models available for users. However, different types of models possess different form and structure as well as complexity of computation. It is difficult for users to select an appropriate model for a specific application without a clear understanding of the limitations or strengths for each model or tool. This review evaluates 14 more commonly used watershed-scale NPS pollution models to explain how and when the application of these different models are appropriate for a given effort. The models that are assessed have a wide range of capacities that include simple models used as rapid screening tools (e.g., Long-Term Hydrologic Impact Assessment (L-THIA) and Nonpoint Source Pollution and Erosion Comparison Tool (N-SPECT/OpenNSPECT)), medium-complexity models that require detail data input and limited calibration (e.g., Generalized Watershed Loading Function (GWLF), Loading Simulation Program C (LSPC), Source Loading and Management Model (SLAMM), and Watershed Analysis Risk Management Frame (WARMF)), complex models that provide sophisticated simulation for NPS pollution processes with intensive data and rigorous calibration (e.g., Agricultural Nonpoint Source pollution model (AGNPS/AnnAGNPS), Soil and Water Assessment Tool (SWAT), Stormwater Management Model (SWMM), and Hydrologic Simulation Program Fortran (HSPF)), and modeling systems that integrate various sub-models and tools, and contain the highest complexity to solve all phases of hydrologic, hydraulic, and chemical dynamic processes (e.g., Automated Geospatial Watershed Assessment Tool (AGWA), Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) and Watershed Modeling System (WMS)). This assessment includes model intended use, components or capabilities, suitable land-use type, input parameter type, spatial and temporal scale, simulated pollutants, strengths and limitations, and software availability. Understanding the strengths and weaknesses of each watershed-scale NPS model will lead to better model selection for suitability and help to avoid misinterpretation or misapplication in practice. The article further explains the crucial criteria for model selection, including spatial and temporal considerations, calibration and validation, uncertainty analysis, and future research direction of NPS pollution models. The goal of this work is to provide accurate and concise insight for watershed managers and planners to select the best-suited model to reduce the harm of NPS pollution to watershed ecosystems.


2010 ◽  
Vol 121-122 ◽  
pp. 198-203
Author(s):  
Yan Chun ◽  
Sheng Xi Li ◽  
Ya Zhou Li

As hierarchical storage is one of the highlights in researching and realizing of mass data storage, this paper mainly describes a study on data storage structure, evaluation of data importance and data management model of hierarchical storage.


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