Knowledge Economy: Model Construction and Development Trend of Online Education

In regard to knowledge economy, the current concept in the model construction of online education, including distance education and online learning, generally refers to a kind of network-based learning behavior, similar to the concept of online training. Compared with traditional offline education methods, through the application of information technology and internet technology for content dissemination and rapid learning, online education has the characteristics of high efficiency, convenience, low threshold, and rich teaching resources. Online education covers a wide range of people, different forms of learning, and its classification methods are more diverse. Online education services are the fastest growing field of education informatization. At the moment, the most pressing problems include effectively integrating educational resources with internet technology, launching online education services and products that are highly interactive and would encourage personalized learning, increasing user stickiness, as well as avoiding trend-following and conceptualized investment.

3D CITYGML BUILDING MODELS DEVELOPMENT WITH CROSS-SCALE QUERY DATABASE

CityGML model-based is now a norm for smart city or digital twin city development for better planning, management, risk-related modelling and other applications. CityGML comes with five levels of details (LoD, in version 2.0) of buildings. The LoDs are also known as pre-defined multi-scale models requiring a large storage-memory-graphic consumption than a single scale model. LoD CityGML models are primarily constructed using point cloud measurements and images of multiple systems, resulting in a range of accuracies and detailed model representations. Additionally, it entails several software, procedures, and formats for the construction of the respective LoDs prior to the final result in the CityGML schema. Thus, this paper discusses several issues of accuracy and consistency, proposing several quality controls (QC) for multiple data acquisition systems (e.g. airborne laser systems and mobile laser systems), model construction techniques (e.g. LoD1, LoD2, and LoD3), software (interchange formats), and migration to a PostgreSQL database. Additionally, the paper recommends the importance of minimising implementation errors. A scale-specific unique identifier is introduced to link all associated LoDs, enabling cross-LoD information queries within a database. Proper model construction, accuracy control, and format interchange of LoD models in accordance with national and international standards will undoubtedly encourage and expedite data sharing among data owners, agencies, stakeholders, and public users. A summary of the work and accomplishments is included, as well as a plan for future research on this subject.

A Model for Performance Evaluation

As a result of the parallel element setting, performance assessment and model construction are constrained. Component functions should be observable without direct connections to programming language, for example. As a result of this, solutions that are constituted interactively at program execution necessitate recyclable performance-monitoring interactions. As a result of these restrictions, a quasi, coarse-grained Performance Evaluation (PE) approach is described in this paper. A performance framework for the application system can be polymerized from these data. To validate the evaluation and model construction techniques included in the validation framework, simplistic elements with well-known optimization models are employed.

Pea Grain Protein Content Across Italian Environments: Genetic Relationship With Grain Yield, and Opportunities for Genome-Enabled Selection for Protein Yield

Wider pea (Pisum sativum L.) cultivation has great interest for European agriculture, owing to its favorable environmental impact and provision of high-protein feedstuff. This work aimed to investigate the extent of genotype × environment interaction (GEI), genetically based trade-offs and polygenic control for crude protein content and grain yield of pea targeted to Italian environments, and to assess the efficiency of genomic selection (GS) as an alternative to phenotypic selection (PS) to increase protein yield per unit area. Some 306 genotypes belonging to three connected recombinant inbred line (RIL) populations derived from paired crosses between elite cultivars were genotyped through genotyping-by-sequencing and phenotyped for grain yield and protein content on a dry matter basis in three autumn-sown environments of northern or central Italy. Line variation for mean protein content ranged from 21.7 to 26.6%. Purely genetic effects, compared with GEI effects, were over two-fold larger for protein content, and over 2-fold smaller for grain and protein yield per unit area. Grain yield and protein content exhibited no inverse genetic correlation. A genome-wide association study revealed a definite polygenic control not only for grain yield but also for protein content, with small amounts of trait variation accounted for by individual loci. On average, the GS predictive ability for individual RIL populations based on the rrBLUP model (which was selected out of four tested models) using by turns two environments for selection and one for validation was moderately high for protein content (0.53) and moderate for grain yield (0.40) and protein yield (0.41). These values were about halved for inter-environment, inter-population predictions using one RIL population for model construction to predict data of the other populations. The comparison between GS and PS for protein yield based on predicted gains per unit time and similar evaluation costs indicated an advantage of GS for model construction including the target RIL population and, in case of multi-year PS, even for model training based on data of a non-target population. In conclusion, protein content is less challenging than grain yield for phenotypic or genome-enabled improvement, and GS is promising for the simultaneous improvement of both traits.