Teaching Design on Digital Environment of Intelligence Learning

The practice and research on the establishment of digital course environment and the reform of learning way breaks through the integration of information technology and teaching courses. Digital course environment promotes the teaching interest and becomes the learning under the support of learning terminal, which must make students happy. The digitalization of teaching materials, platform of learning and learning according to requirements promotes the establishment of happy class. Establishment of learning environment is the basis of realizing the reform of learning and teaching ways. With the rapid development of information technology, intelligence learning is the necessary outcome of deep integration with education learning.

Environmental Analysis Using Integrated GIS and Spatial Configurations in Israel

The scope for environmental analysis constitutes a critical factor in recent times, yet demanding importance due to the concerns of environmental sustainability. The study aims at analysing the prospects of implementing an integrated GIS and spatial configuration for environment analysis in Israel. The study adopts an empirical study design to consider the multi-dimensional utilisation of an integrated GIS and spatial configuration for environment analysis. The study considers the materials and methods of the GIS system modelling as well, consisting of satellite imagery, GPS-based location identification, Esri ArcGIS, CyberGIS, and BIM integration to present a comprehensive system for the environmental analysis of Israel. The results of the study indicate that the threats of natural disasters and climate change can be identified based on the synergy of spatial data within an integrated GIS modelling. In many cases, it is also used in collaboration with a BIM to ensure that planning and decision-making processes are sustainable, economically beneficial and environmentally considered. Thus, it is concluded that environmental analysis through the projection of visually represented satellite imagery within an integrated GIS with spatial configurations in Israel can minimise the conflicts between the infrastructural designs, human activities, and environmental sustainability.

Vision‐audio fusion SLAM in dynamic environments

Moving humans,agents,and subjects bring many challenges to robot self‐localisation and environment perception.To adapt to dynamic environments,SLAM researchers typically apply several deep learning image segmentation models to eliminate these moving obstacles.However,these moving obstacle segmentation methods cost too much computation resource for the onboard processing of mobile robots.In the current industrial environment,mobile robot collaboration scenario,the noise of mobile robots could be easily found by on‐board audio‐sensing processors and the direction of sound sources can be effectively acquired by sound source estimation algorithms,but the distance estimation of sound sources is difficult.However,in the field of visual perception,the 3D structure information of the scene is relatively easy to obtain,but the recognition and segmentation of moving objects is more difficult.To address these problems,a novel vision‐audio fusion method that combines sound source localisation methods with a visual SLAM scheme is proposed,thereby eliminating the effect of dynamic obstacles on multi‐agent systems.Several heterogeneous robots experiments in different dynamic scenes indicate very stable self‐localisation and environment reconstruction performance of our method.

An Intelligent Agent Based on Virtual Geographic Environment System

On the basis of previous work, this paper designs an intelligent agent based on virtual geographic environment (VGE) system that is characterized by huge data, rapid computation, multi\|user, multi\|thread and intelligence and issues challenges to traditional GIS models and algorithms. The new advances in software and hardware technology lay a reliable basis for system design, development and application.

Deep Learning Based Energy Consumption Prediction on Internet of Things Environment

The creation of national energy strategy cannot proceed without accurate projections of future electricity consumption;this is because EC is intimately tied to other forms of energy,such as oil and natural gas.For the purpose of determining and bettering overall energy consumption,there is an urgent requirement for accurate monitoring and calculation of EC at the building level using cutting-edge technology such as data analytics and the internet of things(IoT).Soft computing is a subset of AI that tries to design procedures that are more accurate and reliable,and it has proven to be an effective tool for solving a number of issues that are associated with the use of energy.The use of soft computing for energy prediction is an essential part of the solution to these kinds of challenges.This study presents an improved version of the Harris Hawks Optimization model by combining it with the IHHODL-ECP algorithm for use in Internet of Things settings.The IHHODL-ECP model that has been supplied acts as a useful instrument for the prediction of integrated energy consumption.In order for the raw electrical data to be compatible with the subsequent processing in the IHHODL-ECP model,it is necessary to perform a preprocessing step.The technique of prediction uses a combination of three different kinds of deep learning models,namely DNN,GRU,and DBN.In addition to this,the IHHO algorithm is used as a technique for making adjustments to the hyperparameters.The experimental result analysis of the IHHODL-ECP model is carried out under a variety of different aspects,and the comparison inquiry highlighted the advantages of the IHHODL-ECP model over other present approaches.According to the findings of the experiments conducted with an hourly time resolution,the IHHODL-ECP model obtained a MAPE value of 33.85,which was lower than those produced by the LR,LSTM,and CNN-LSTM models,which had MAPE values of 83.22,44.57,and 34.62 respectively.These findings provided evidence of the IHHODL-ECP model’s improved ability to provide accurate forecasts.

INTELLIGENT MECHANISM TO SUPPORT DFX ABILITIES IN AUTOMATED DESIGNER'S ENVIRONMENT

The paper aims at providing a computerized design environment to support product design practically. The authors solved this problem by taking the product life-cycle issues into consideration as more as possible during the design process from the designer-oriented perspective of view. Design for X-abilities (DFX) is an effective approach to this philosophy. So the paper mainly presents the infrastructure of an intelligent DFX mechanism which is the essential part of the developed product design environment. At first the designer-oriented computer environment DesignerSpace is introduced for understanding the designer how to implement design activities and DFX method better. In order to integrate design knowledge from downstream aspects for the optimization and the design decision-making, an intelligent DFX mechanism is developed to incorporate knowledge base, algorithm-base and monitoring/debugging tools. DesignerSpace is implemented with DFX abilities and applied to the blisk design of aircraft engine and the further development is strongly intended.

Review on the Sensor Technology Applied in the Intelligent Learning Environment

The development of sensor technology promotes the transformation of the intelligent learning environment. Through the research of the sensor technology application, this paper described the intelligent learning environment application system of the sensor technology and the management functions, conference organization, a library building, information collection, monitoring and equipment sharing function the role of sensor technology played in the intelligent learning environment.

Design and Implementation of an Intelligent Monitoring and Early Warning System for Kitchen Garbage Treatment

With a population of 1.4 billion in China and a huge daily output of kitchen waste,intelligent treatment of kitchen waste is imperative.This article elaborates on the design and implementation of an intelligent monitoring and early warning system from five aspects:system architecture design,hardware equipment selection and configuration,data collection and processing flow,early warning algorithm and model development,and system integration and testing verification.It also points out the advantages of the intelligent monitoring and early warning system in kitchen waste treatment.

Research on the Multi-Interactive Intelligent Teaching Model of College English in the Information Technology Environment

The multi-interactive teaching mode based on the information technology is a new teaching mode, which promotes students' autonomous learning and research-oriented learning through the online and offline effective interaction in and out of class, fully embodying the principle of the learning-orientation. Based on this, this paper focuses on the connotation and the theoretical basis o f the multi-interactive teaching model, as well as its implementation practices and characteristics, with a view o f providing help to improve the quality of the college English teaching.

Design of an Information Security Service for Medical Artificial Intelligence

The medical convergence industry has gradually adopted ICT devices,which has led to legacy security problems related to ICT devices.However,it has been difficult to solve these problems due to data resource issues.Such problems can cause a lack of reliability in medical artificial intelligence services that utilize medical information.Therefore,to provide reliable services focused on security internalization,it is necessary to establish a medical convergence environment-oriented security management system.This study proposes the use of system identification and countermeasures to secure systemreliabilitywhen using medical convergence environment information in medical artificial intelligence.We checked the life cycle of medical information and the flow and location of information,analyzed the security threats that may arise during the life cycle,and proposed technical countermeasures to overcome such threats.We verified the proposed countermeasures through a survey of experts.Security requirements were defined based on the information life cycle in the medical convergence environment.We also designed technical countermeasures for use in the security management systems of hospitals of diverse sizes.

Paving the Way for Economically Accepted and Technically Pronounced Smart Radio Environment

Recently,Reconfigurable Intelligent Surfaces(RISs)have been introduced to provide the necessary flexibility for the design of the Smart Radio Environment(SRE),which can be optimally shaped to facilitate efficient signal transmissions.In line with the concept of smart cities,SRE needs to be carefully designed with respect to the city infrastructure and utilization of resources.In this paper,we provide our vision on RIS integration into future Smart Cities by highlighting the potential technical,environmental,and economic motivations of RIS deployment in harmony with various ecosystems at a city level such as buildings facades.To this end,we are pointing out some scenarios for mitigating the conflict between RIS realization and the existing building facade’s ecosystems such as advertising display and solar cells on building walls.Also,in this fashion,the proposed vision supports a win-win relationship between all stakeholders of different ecosystems.This study presents guidelines for not only enabling seamless economically accepted RIS widespread utilization but,also more technically sounding SRE by supporting enhanced RIS features and more advanced applications that cannot be attained by traditional passive RIS.Moreover,based on the current research directions,we offer promising insights for cost-effective mass pro-duction through motivating two scenarios of“all on silicon”and“all as metasurface”fabrication technology.With this study,we aim to encourage the metasurface researchers,that for a broad deployment of the technical solution,economic,environmental,and other commercial requirements should be planned together,early on in the design phase.

Hybrid Deep Learning Enabled Air Pollution Monitoring in ITS Environment

Intelligent Transportation Systems(ITS)have become a vital part in improving human lives and modern economy.It aims at enhancing road safety and environmental quality.There is a tremendous increase observed in the number of vehicles in recent years,owing to increasing population.Each vehicle has its own individual emission rate;however,the issue arises when the emission rate crosses a standard value.Owing to the technological advances made in Artificial Intelligence(AI)techniques,it is easy to leverage it to develop prediction approaches so as to monitor and control air pollution.The current research paper presents Oppositional Shark Shell Optimization with Hybrid Deep Learning Model for Air Pollution Monitoring(OSSOHDLAPM)in ITS environment.The proposed OSSO-HDLAPM technique includes a set of sensors embedded in vehicles to measure the level of pollutants.In addition,hybridized Convolution Neural Network with Long Short-Term Memory(HCNN-LSTM)model is used to predict pollutant level based on the data attained earlier by the sensors.In HCNN-LSTM model,the hyperparameters are selected and optimized using OSSO algorithm.In order to validate the performance of the proposed OSSO-HDLAPM technique,a series of experiments was conducted and the obtained results showcase the superior performance of OSSO-HDLAPM technique under different evaluation parameters.

Design Path of Ecological Learning Environment Based on Spatial Resilience

Nowadays,the city’s focus on education makes the improvement of learning environment become a new demand for development.From the the perspective of ecology,the theory of"resilience"is introduced to break the stereotype of the existing learning environment and create a space for dialogue with nature from inside to outside.At the same time,the learning environment is divided into observation learning space,exploration learning space and communication learning space by theory and method of multiple intelligence integrating teaching and learning.Through the analysis on resilience characteristics of three types of space,eight basic unit forms of learning environment design are obtained.Arrangement and combination of its form can improve the campus environment,increase children’s learning efficiency and the risk response ability of campus environment,and give children the opportunity to interact with and understand nature in the learning process,so as to provide reference for the diversified development of education and learning space.

Research on Novel and Innovative Music Education Model based on Multiple Intelligences Theory and New Media

With the rapid development of new media and education theories, the combination of the two aspects is urgently needed. In this paper, we conduct theoretical analysis on novel and innovative music education model based on multiple intelligences theory and new media. The theory of multiple intelligence education concept is to change too pay attention to the tendency of knowledge. The novelty of new media, not only in the form of new information carrier and communication channel, also include technological progress brings new propagation mode. Our proposed combined model will enhance the performance of the current teaching activity which is meaningful.

Intelligent Color Reasoning of IOT Based on P-laws

Aiming at the dynamics and uncertainties of natural colors affected by the natural environment,a color P-law generation model based on the natural environment is proposed to develop algorithms and to provide a theoretical basis for plant dynamic color simulation and color sensor data transmission.Based on the HSL(Hue,Saturation,Lightness)color solid,the proposed method uses the function P-set to provide a color P-law generation model and an algorithm of the Dynamic Colors System(DCS),establishing the DCS modeling theory of the natural environment and the color P-reasoning simulation based on the HSL color solid.The experimental results show that based on the color P-law,for the DCS of the natural environment,when the external factors change,the color of the plant changes,accordingly,verifying the effectiveness of the color P-law generation model and the algorithm of the DCS.In the dynamic color intel-ligent simulation system,when external factors change,the dynamic change of plant color generally conforms to the basic laws of the natural environment.This enables the effective extraction of color data from the Internet of Things(IoT)-based color sensors and provides an effective way to significantly reduce the data transmission bandwidth of the IoT network.

从知识困境到认知陷阱:生成式技术驱动型信息生态系统安全问题研究

生成式技术驱动型信息生态系统以生成式人工智能技术为核心,对整个信息环境中的知识传递与共享、认知流动与扩散过程发挥支撑和推动作用。然而,这种创新型的信息生态系统也伴随着知识安全和认知安全问题的出现。本文从知识环境和认知环境两个层面入手,对生成式技术驱动型信息生态系统的特点、优势与风险进行深入剖析,探索如何在符合人类价值观和社会伦理的前提下,充分发挥生成式人工智能的潜力,推动构建高效、安全、可持续发展的生成式技术驱动型信息生态系统。

多源遥感数据在战场环境智能态势感知的现状及展望

面对复杂战场环境信息的快速变化,及时全面准确地掌握复杂战场环境态势,是未来打赢信息化战争的前提条件。为了探索多源遥感数据对战场环境态势感知的发展方向,基于广泛调研战场环境态势感知的遥感需求,首先对战场环境态势智能感知的概念和内涵进行了阐述,然后对多源遥感数据的处理与战场态势感知应用现状进行概述,分析了遥感在战场态势智能感知面临的挑战,最后提炼总结了遥感在战场态势感知的进展和发展趋势。遥感为战场环境态势感知提供多种观测数据,遥感与人工智能算法结合可以为军事战场环境态势感知提供多种应用,为指挥人员决策提供数据支持,但仍然存在大量挑战需要解决。在分析现阶段成果和面临挑战的基础上,提出了遥感在战场环境智能态势感知的前瞻,指出了基于遥感的深度学习可解释性和智慧战场是遥感在战场智能态势感知发展所面临的困难。

数智环境下社交媒体用户算法素养评价指标体系构建研究

[目的/意义]构建社交媒体用户算法素养评价指标体系,科学地测量社交媒体的算法素养,发现社交媒体用户算法素养存在的问题,进而展开有针对性的算法素养教育。[方法/过程]采用文献研究法、专家调查法以及层次分析法,根据国内外相关研究成果,从算法意识与态度、算法知识、算法技能、算法规范4个维度构建社交媒体用户算法素养评价指标体系,并对算法素养评价指标权重进行分析,为提升社交媒体用户算法素养提出有针对性的建议和策略。[结果/结论]通过对社交媒体用户算法素养评价指标体系分析,未来可以从三个方面提升社交媒体用户的算法素养:将算法素养纳入通识教育体系;以风险教育为切入点加强算法风险知识与算法风险控制能力的培养;丰富算法素养教育与培训的形式。

双中心模式:数智环境下红色档案治理模式探析

数智环境为红色档案实现从管理到治理的转变创造了有利条件,论文分析了现阶段红色档案管理面临着“事由”与“来源”和“单一”与“多元”的双重困境,并在此基础上提出红色档案治理的“双中心”治理模式。一方面,通过建立数字全宗和进行智能管理实现“以数字全宗为中心”的内部治理;另一方面,通过构建用户画像和收集用户反馈实现“以用户交互为中心”的外部治理,并将移动互联技术应用于红色档案治理的全过程,以期促进红色档案活化、社会记忆构建和文化基因传承,为相关理论研究和实践探索提供参考借鉴。

高校智慧教育生态体系构建

智慧教育是教育信息化的最终目标和最高形态,高校作为培养高层次创新人才的主要阵地,应深入推进智慧教育。在分析高校智慧教育内涵及特征的基础上,针对高校智慧教育实践中存在的主要问题,从目标层、运用层、支持层和基础层构建高校智慧教育生态体系,并从夯实硬件环境建设、强化管理服务平台和整合智慧应用场景等方面提出具体建设内容。