Cartography includes two major tasks: map making and map application, which is inextricably linked to artificial intelligence technology. The cartographic expert system experienced the intelligent expression of symbolism. After the spatial optimization decision of behaviorism intelligent expression, cartography faces the combination of deep learning under connectionism to improve the intelligent level of cartography. This paper discusses three problems about the proposition of “deep learning + cartography”. One is the consistency between the deep learning method and the map space problem solving strategy, based on gradient descent, local correlation, feature reduction and non-linear nature that answer the feasibility of the combination of “deep learning + cartography”; the second is to analyze the challenges faced by the combination of cartography from its unique disciplinary characteristics and technical environment, involving the non-standard organization of map data, professional requirements for sample establishment, the integration of geometric and geographical features, as well as the inherent spatial scale of the map; thirdly, the entry points and specific methods for integrating map making and map application into deep learning are discussed respectively.
Synthesis of macro-mesoporous Titania (Titanium dioxide-TiO2) nanospheres was successfully achieved using a modified template-free methodology to incorporate macroporous channels into a mesoporous TiO2 framework to form mixed macro-mesoporous TiO2 spheres (MMPT), which were doped with carbon dots (C-dots) to form improved nanocomposites (C-dots@MMPT). Elemental composition, surface bonding and optical properties of these nanocomposites were characterized by X-ray diffraction (XRD), Fourier transforms infrared spectroscopy (FTIR) and ultraviolet-visible absorption spectroscopy (UV-VIS). Evaluation of photocatalytic activity for each (C-Dots@MMPT) sample was performed via degrading the Methylene Blue (MB) dye compared with bare samples (MMPT) under visible light irradiation using 300 Watt halogen lamp.
This paper provides insight into innovation energy, its five working mechanisms, and innovative work behaviour (IWB). Although human energy is often mentioned as an important factor in theories about motivation, it is still an unexplored theme in literature. The management of organisations often focuses on the innovation content and neglects the process aspects. Strategic and operational HRM involvement is needed to realising the essential conditions for the innovation energy of innovative employees. An abductive case study on innovation energy took place in five educational departments of one academy at Saxion University of Applied Sciences in the Netherlands. We interviewed 21 innovating lecturers and their five team leaders individually and organised five focus groups with a total of 17 team members. Innovation energy converts individual innovation properties (creativity, psychological empowerment, and optimism) into IWB. Organisations must pay attention to these properties and four other working mechanisms (autonomy, teamwork, leadership, and external contacts) that influence this conversion process. HRM professionals should be involved with innovation processes to realise the right conditions for innovation energy, together with line management. The construct of innovation energy with five working mechanisms gives more insight into the IWB process from the perspective of the engaged employee with IWB. This research contributes to the body of knowledge on IWB, (human) innovation energy, and engagement in relation to HRM.
The existing ample literature studied the factors for adopting computer-assisted audit techniques (CAATs) by internal and external auditors, frequently ignoring their impact on the quality of audits and companies’ efficiency. This study delivers new evidence on the kinds of CAATs utilized by internal auditors, examines their adoption impact on corporate sustainability, and studies the moderating impact of company characteristics. This study used data from internal auditors in Ethiopia gathered using a survey, and the study hypotheses were tested using the partial least squares-structural equation modeling (PLS-SEM) technique. The study found a moderate utilization of CAATs by internal auditors in executing their activities. The result also revealed a highly positive impact of internal auditors’ CAAT utilization on fraud discovery in the acquisition process. The study found that the intensity of this relationship is impacted by the companies’ characteristics of management commitment. However, the size and type of the company are not impacting it. This study finding complements prior studies and helps practitioners make decisions that can improve CAAT utilization in internal audit functions for a high level of companies’ sustainability.
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