Jing-Doo Wang¹, Chayadi Oktomy Noto Susanto^1,2,*

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3097-3112, 2023, DOI:10.32604/cmc.2023.040914

Abstract Predicting traffic flow is a crucial component of an intelligent transportation system. Precisely monitoring and predicting traffic flow remains a challenging endeavor. However, existing methods for predicting traffic flow do not incorporate various external factors or consider the spatiotemporal correlation between spatially adjacent nodes, resulting in the loss of essential information and lower forecast performance. On the other hand, the availability of spatiotemporal data is limited. This research offers alternative spatiotemporal data with three specific features as input, vehicle type (5 types), holidays (3 types), and weather (10 conditions). In this study, the proposed model combines the advantages of the… More >

He Gong^1,2,3,4, Ji Li¹, RuiWen Ni¹, Pei Xiao¹, Hang Ouyang¹, Ye Mu^1,*, Thobela Louis Tyasi⁵

Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 1049-1062, 2021, DOI:10.32604/iasc.2021.019730

Abstract Presently, the adoption of Internet of things(IOT)-related technologies in the Smart Farming domain is rapidly emerging. The increasing number of sensors used in diverse applications has provided a massive number of continuous, unbounded, rapid data and requires the management of distinct protocols, interfaces and intermittent connections. A low-cost, low-power, and low data-rate solution is proposed to fulfill the requirements of information monitoring for actual large-scale agricultural farms, which we will need pressingly in the future. This paper designs a heterogeneous data acquisition and control system for differentiated agricultural information monitoring terminal. Based on the IoT-CAN bus architecture, the system can… More >

Toshihiro Ashino^1,*, Nobutaka Nishikawa²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.22, No.2, pp. 137-137, 2019, DOI:10.32604/icces.2019.05454

Abstract Materials performance analysis process requires integration of many heterogeneous data and information resources, e.g. experimental data, empirical models and computational simulation. Virtual Research Environment (VRE) for materials science and engineering should support each data handling processes, data retrieval, conversion, statistical analysis, symbolic manipulation and visualization within single interactive and scripting environment.
Furthermore, in order to integrate heterogeneous data, it requires a common dictionary which describe semantic relationships among these data resources. It is required to identify corresponding data items from different data resources. It can be a flat structured table, but an ontology which describes semantic relationships among concepts,… More >