Papers by Keyword: Data

Abstract: This study developed a user-friendly and simplified Spatial Decision Support System using Geographic Information System (GIS) techniques to provide essential information for road managers. This enables the application of appropriate treatments at the right time, based on the available budget. A Global Positioning System (GPS) device was used to collect coordinate data for designated routes within Akure metropolis. Twenty (20) different roads were selected for the study. Data such as road names, coordinates, distances, and infrastructure or facilities unique to each road were collected through reconnaissance surveys, GPS tools, administrative road maps of the city, and street guides clearly showing Akure’s road network. The data were processed using Microsoft Excel, and classifications of the selected roads were made for easy referencing. Database design and creation were carried out using GIS tools within the ArcGIS environment. Digitization of data, labeling of features, symbology, layout design, hyperlinking, and other spatial features were implemented using ArcGIS applications. Each road was linked to its characteristic information, allowing users to access and update information as needed. The result shows that 95% of the total selected roads lack traffic lights and pedestrian bridge facilities. Forty-five percent of the roads have street light facilities. 5% of the road has traffic light facilities. 75% have no bus shelters. Only 5% of the total selected roads have all the identified road facilities. It was concluded that some of the selected roads were not in good condition. While some road facilities were defective, other roads lacked the necessary road facilities that could aid traffic flow. However, the data and associated attributes of each road can be used to support administrative decisions regarding maintenance.

Abstract: Studying the behaviour of engineering systems and processes from the perspective of applications of artificial intelligence provides an invaluable reference to improve their productivity and industrial development at large. This study comprehensively unveiled the problems faced by engineering systems and how artificial intelligence could be deployed as a technique for the future advancement of the industry. A brief background of the application of artificial intelligence in some selected engineering fields revealed that insufficient operational and process data from both plants and processes are major problems causing the survival of sustainable intelligent systems thereby, leading to incessant system failure. Furthermore, it was equally discovered that artificial intelligent for specific application are based on the data obtained from such application. Thus, there is no universally agreed artificial intelligent for a specific application. This made it a bit complex in developing intelligent systems. Keywords: Artificial Neural Network, Applications, Engineering, Training, Data.

Abstract: Today's and tomorrow's secret data exchange relies heavily on cryptography. Cryptographic applications offer a secure communication channel for safely transferring data. It provides individuals, groups, and organizations with greater privacy and access to communication and other information, as well as the opportunity to restore personal privacy. Nowadays, online users desire to create an account in order to get access to certain websites, such as online tutorials, online purchases, online resource access, hosting services, social networking sites, and so on. However, unless the service provider or authority person ensures that the registration and login processes are genuine, there is a potential that the account might be hacked by a third party using the ordinary user access method. With the growing usage of cloud emails and frequent reports of large-scale leakage occurrences, a security attribute known as forward secrecy becomes desired and necessary for both users and cloud service providers to improve the security of cloud email systems.

Abstract: Estimating the state-of-charge of a lead-acid battery at remote seismic nodes is a key factor in managing the available power. Optimal management enables the continuous acquisition of seismic data of an area. This paper presents the management of lead-acid batteries at remote seismic nodes, using the Neural Network model's historical data to estimate the battery's state-of-charge. Powersim (PSIM) simulation tool was used to implement photovoltaic energy harvesting system with a buck mode converter and maximum power point tracking algorithm to acquire historical data. A backpropagation neural network technique for training the historical dataset of hourly points in 500 days on the Matlab platform is adopted, and a feedforward neural network is employed due to the irregularities of the input data. The neural network model's hidden layer contains the transfer function of the Tansig Function to produce the model output of state-of-charge estimations. Besides, this paper is based on the management of estimating the state-of-charge of the lead-acid battery near-realtime instead of relying on the vendor's lifecycle information. The simulated results show the simplicity and optimal estimations of state-of-charge of the lead-acid battery with RMSE of 0.023%.

Abstract: A semi-empirical model has been investigated to represent household compressors. The model based on calorimeter data for two distinguished brand (Danfoss and Electrolux CUBIGEL) and compared with eight brands consisting of ninety compressors model. The calorimeter data are correlated (according to ARI standard 540-90 [1] and working refrigeration temperature cycle for ASHRAE Technical Committee 8.9[2]) as a function of refrigerant saturated evaporating temperatures from (-35 to 10) °C and swept volume range (2.24-11.15) cm³ keeping of the refrigerant saturated condensing temperature constant at 54.5 °C. The correlations were found with ten-coefficient polynomial by using Matlab software – surface fitting method for cooling capacity, power consumption, and refrigerant mass flow rate.In addition, other equations for cooling capacity, power consumption, and refrigerant mass flow rate at-23.3 °C evaporator temperature, 54.4 °C condenser temperature, and 32 °C temperature for liquid line which is the base points of the refrigerator cycle according to ASHRAE[2] , cover the range (2.42-11.15) cm³ swept volume which are created to quick choose the proper compressor.The result indicated that the surface fitting models are accurate within ± 15% deviation of compressors data of seventy-two models for cooling capacity, fifty models for power, and twenty-five models for refrigerant mass flow rate.

Abstract: This paper analyzes the present highway situation of remote areas in Inner Mongolia that traditional charge cannot meet the demand. According to the advanced communication technologies of highway and the data transmission requirement for highway communication system, we introduced a method of data transfer based on .NET Framework. The results show that adopting VB.NET and SQL Server 2005, the data of wireless transmission between toll station and sub-center security has been obtained, and the stability of the system has been analyzed.

Abstract: Efficient data mining model design for a large database in the cloud computing environment is studied. For large databases efficiently mining problem, an efficient data mining model in the cloud computing environment based on improved manifold learning algorithms is proposed. The use of nonlinear manifold learning algorithms is able to reduce dimensionality of data vector feature in cloud computing environments, through characteristic extraction module to preprocess data, improved classical manifold learning algorithm is adopted to increase the distance between the data of sample spread intensive area and shorten the distance between the data of sample spread sparse area, prompting even overall distribution of sample database under cloud computing environment, so as to achieve accurate mining for efficient data in cloud computing environment. The experimental results show that the proposed method can accurately mine target data under cloud computing environments, with high efficiency and precision.

Abstract: data information management has thoroughly changed the traditional mode of data management, whose real ability is not only presented on a more efficient work way, but also on the creation of a new work approach, which is the core content of department work flow reorganization, and also the embodiment of the ultimate goal of department workflow reorganization. With the continuous development of enterprise information, the establishment shall be constantly perfected of data management information system.

Abstract: Through collecting real liquefaction in-situ data available worldwide, the correlations of influencing characteristics parameters such as PGA, water table depth, buried depth of sandy layer, SPT counts and shear wave velocity with respect to liquefaction were analyzed by means of Pearson correlation method. The correlative performance of the characteristic parameters with liquefaction was comparatively analyzed under conditions of varying buried depths, water tables and seismic intensities. The real correlations of the characteristic parameters with liquefaction were obtained corresponding to real dynamic loading, real buried condition and in-situ testing data. The analytical results show that water table, buried depth of sandy layer, SPT and shear wave velocity keep negative correlations with respect to liquefaction while correlation of PGA with liquefaction was positive. The correlations of buried depth of sandy layer, SPT were remarkable while the correlations of water table, shear wave velocity were weak. The correlation coefficient of SPT was the largest, followed by buried depth of sandy layer, PGA and water table; and the correlation coefficient of shear wave velocity was the smallest. The results presented herein can be used for updating the liquefaction evaluation methods in the codes.

Abstract: In recent years, the development of digital libraries also encountered a lot of problems, the cloud computing was applied to digital libraries can solve the problem of information on demand and optimal scheduling of resources and transaction processing capabilities effectively, So as to achieve the purpose of improving the efficiency of resource of digital library and information security. From the digital library of cloud computing and personalized information services status in this paper, the study and found a problem about the digital library information services at this stage, let the virtualization cloud computing, the key technology of distributed data storage, massive data processing and cloud platforms used in building digital library of personalized information service with cloud platform, and deployment cloud services on the platform.