This contribution aims to appraise, analyze and evaluate the literature relating to the interaction of electromagnetic fields (EMF) with matter and the resulting thermal effects. This relates to the wanted thermal effects via the application of fields as well as those uninvited resulting from exposure to the field. In the paper, the most popular EMF heating technologies are analyzed. This involves on the one hand high frequency induction heating (HFIH) and on the other hand microwave heating (MWH), including microwave ovens and hyperthermia medical treatment. Then, the problem of EMF exposure is examined and the resulting biological thermal effects are illuminated. Thus, the two most common cases of wireless EMF devices, namely digital communication tools and inductive power transfer appliances are analyzed and evaluated. The last part of the paper concerns the determination of the different thermal effects, which are studied and discussed, by considering the governing EMF and heat transfer (or bio heat) equations and their solution methodologies.

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.

Spectrum map is the foundation of spectrum resource management, security governance and spectrum warfare. Aiming at the problem that the traditional spectrum mapping is limited to two-dimensional space, a three-dimensional spectrum data acquisition and mapping system architecture for the integration of space, sky and earth is presented, and a spectrum map reconstruction scheme driven by propagation model is proposed, which can achieve high-precision three-dimensional spectrum map rendering under the condition of sparse sampling. The spectrum map reconstructed by this method in the case of single radiation source and multiple radiation sources is in good agreement with the theoretical results based on ray tracing method. In addition, the measured results of typical scenes further verify the feasibility of this method.

The provision of infrastructure and related services in developing Asia via public–private partnership (PPP) increased rapidly during the late 1990s. Theoretical arguments support the potential economic benefits of PPPs, but empirical evidence is thin. This paper develops a framework identifying channels through which economic gains can be derived from PPP arrangement. The framework helps derive an empirically tractable specification that examines how PPPs affect the aggregate economy. Empirical results suggest that increasing the ratio of PPP investment to GDP improves access to and quality of infrastructure services, and economic growth will potentially be higher. But this optimism is conditional, especially on the region’s efforts to further upgrade its technical and institutional capacity to handle complex PPP contracts.