Meta-Heuristic Feature Optimization for ontology-based data security in a campus workplace with robotic assistance.

BACKGROUND: For campus workplace secure text mining, robotic assistance with feature optimization is essential. The space model of the vector is usually used to represent texts. Besides, there are still two drawbacks to this basic approach: the curse and lack of semantic knowledge. OBJECTIVES: This paper proposes a new Meta-Heuristic Feature Optimization (MHFO) method for data security in the campus workplace with robotic assistance. Firstly, the terms of the space vector model have been mapped to the concepts of data protection ontology, which statistically calculate conceptual frequency weights by term various weights. Furthermore, according to the designs of data protection ontology, the weight of theoretical identification is allocated. The dimensionality of functional areas is reduced significantly by combining standard frequency weights and weights based on data protection ontology. In addition, semantic knowledge is integrated into this process. RESULTS: The results show that the development of the characteristics of this process significantly improves campus workplace secure text mining. CONCLUSION: The experimental results show that the development of the features of the concept hierarchy structure process significantly enhances data security of campus workplace text mining with robotic assistance.

A programmable microscopic stage: Design and development.

Microscopes have become a significant part of pathological study. Currently, motorized microscopes are enabled with horizontal and vertical movements, with the facility of fast response in acquiring images or videos from the slide. During microbial screening, viewing the specimen needs following a directional path viz., zig-zag, inward spiral, meander, and so forth. Even though the motorized movements are built-in, human intervention is required while screening. This leads to time delay in the scanning process and may leave some portions of the specimen unattended. In this proposed system, a programmable framework to define the scanning direction for the specimen and a firmware to control the microscopic stage is implemented, to enable customization of the scanning pattern without any human intervention during complete course of screening. The user can define the customized scanning pattern using two-dimensional (2D) graphics drawing primitives. The final drawing is converted into preparatory codes through a micro-computer numeric controlled software, which extracts the address information relating to the movement and direction of the stage. These X, Y directional information are fed into the machine control unit for activating the linear driving system, which has servo drives and motors to power the spindle for precise microscopic stage movement. The proposed system is cost effective and reduces the reliance on technicians in examining the whole slide. The system is also portable and can be attached to any conventional or fluorescence microscope. Some pre-defined scanning patterns have been tested for the stage movements and validated in this work.