Application of New Concept for Multiple Intelligences Calculation for Personality and Social Groups Comparison Research

A person is considered as information-energy system with a host of feedbacks. The possibility of determining the statistical characteristics in a multiple intelligences profile of various social groups’ representatives using the vibraimage technology is investigated. Theft and alcohol abuse have been chosen as examples of significant social problems including deviant behavior and the trigger of formation of various socially vulnerable groups. The comparative analysis of conscious and unconscious attitudes in multiple intelligences structure of individuals prone to deviant behavior and the control group allows differentiating professional preferences and the impact of society on different social groups.

Research on value co-creation elements in full-scene intelligent service

Compared with common intelligent service,full-scene intelligent service has its uniqueness in high integration,synergy,and technological spillover.However,the traditional service or business model theories cannot precisely elaborate its sociotechnical contextual nature and value creation logic.To fill this knowledge gap,we provide initial insights into the value co-creation logic in full-scene intelligent service by exploring the value co-creation elements using a data-driven text mining approach.We analyzed 171 business reports on the full-scene intelligent service by the topic modeling using the Latent Dirichlet Allocation(LDA).The findings reveal three main clusters:value proposition,participants,and connection platform.This study presents a theoretical framework for a further exploratory case study and quantitative research on full-scene intelligent service.This study also helps small and medium-sized enterprises to explore and exploit value co-creation opportunities.

OpenOffice.org中新功能Intelligent Group的设计开发

简要介绍了开源办公软件OpenOffice.org,然后为它开发了一个新功能Intelligent Group,并给出了架构图,还对其设计思想以及部分实现代码进行了阐述。

Architecture of Intelligent Grouping and Resource Sharing Standard

The Intelligent Grouping and Resource Sharing (IGRS) standard is set to enable intelligent grouping, resource sharing and services collaboration among information devices. An IGRS system adopts open architecture, that is, the devices abide by the IGRS standard are interoperable with devices following other standards such as Universal Plug and Play (UPnP). The IGRS supports multiple application frameworks and special applications. Developers can use an IGRS media application framework with various media format standards, such as AVS and MPEG-2, to develop multimedia applications. Applied among computers, consumer electronics, and communication devices, the IGRS standard can realize resource sharing and services collaboration in a certain range of wired or wireless network domain.

基于Group-Res2Block的智能合成语音说话人确认方法

针对现有说话人确认任务基于自然语音条件下并不适用于智能合成语音的问题,提出一种基于Group-Res2Block的智能合成语音说话人确认方法。首先,设计了Group-Res2Block结构,在Res2Block的基础上将当前分组与相邻前后分组进行合并形成新的分组,以增强说话人局部特征的上下文联系;其次,设计了并行结构的多尺度通道注意力特征融合机制,利用不同大小卷积核实现同一层级的特征在通道维度的特征选择,以获取更具表现力的说话人特征,避免信息冗余;最后,设计了串行结构的多尺度层注意力特征融合机制,构建层结构,将深浅层特征整体进行融合并赋予不同权重,以获取最优的特征表达。为验证所提出特征提取网络的有效性,构建了中英文两种智能合成语音数据集进行消融实验和对比实验。结果表明本文方法在该任务的评价指标精确度(accuracy,ACC)、等错误率(equal error rate,EER)和最小检测代价函数(minimum detection cost function,minDCF)上是最优的。此外,通过对模型泛化性能进行测试,验证了本文方法对未知智能语音算法的适用性。

The Application of Multiple Intelligences Theory in College English Reading Course

This paper,based on Gardner's Multiple Intelligences Theory,aims to investigate whether the application of MI Theory in col lege English reading class can improve students'English reading proficiency.MI-categorized activities are adopted in the class.The paper explores college Enlgish reading teaching strategy based on MI Theory to improve English teaching proficiency.The paper sheds some light on how MI theory could be applied in EFL.

Feature Selection Using Grey Wolf Optimization with Random Differential Grouping

Big data are regarded as a tremendous technology for processing a huge variety of data in a short time and with a large storage capacity.The user’s access over the internet creates massive data processing over the internet.Big data require an intelligent feature selection model by addressing huge varieties of data.Traditional feature selection techniques are only applicable to simple data mining.Intelligent techniques are needed in big data processing and machine learning for an efficient classification.Major feature selection algorithms read the input features as they are.Then,the features are preprocessed and classified.Here,an algorithm does not consider the relatedness.During feature selection,all features are misread as outputs.Accordingly,a less optimal solution is achieved.In our proposed research,we focus on the feature selection by using supervised learning techniques called grey wolf optimization(GWO)with decomposed random differential grouping(DrnDG-GWO).First,decomposition of features into subsets based on relatedness in variables is performed.Random differential grouping is performed using a fitness value of two variables.Now,every subset is regarded as a population in GWO techniques.The combination of supervised machine learning with swarm intelligence techniques produces best feature optimization results in this research.Once the features are optimized,we classify using advanced kNN process for accurate data classification.The result of DrnDGGWO is compared with those of the standard GWO and GWO with PSO for feature selection to compare the efficiency of the proposed algorithm.The accuracy and time complexity of the proposed algorithm are 98%and 5 s,which are better than the existing techniques.

Clinical Intelligent Diagnosis Path Based on the Chief Complaint

Goals of traditional Chinese medicine(TCM)include precision,accuracy,and recognition by clinical practice.Establishment of a diagnosis and treatment system that closely conforms to the principle-method-recipe-medicines system and derivation of an accurate diagnosis and treatment plan should be considerations of TCM.Artificial intelligence research based on computer technology is one of the effective ways to solve this problem.In the research of intelligent diagnosis path,reflecting the characteristics of the overall view and dialectical treatment of TCM such as"Combination of four diagnostic methods""overall examination""combination of disease and syndrome"and"treatment individualized to patient,season and locality"are key for successful research of artificial intelligence in TCM diagnosis or recognition by clinical practice.

一种能够实现双层稀疏性的Group Logarithm模型

稀疏化模型研究是人工智能领域研究的热点之一。对于该问题Lasso模型忽略了变量之间的组结构,只能实现分散的变量选择;Group Lasso也只能实现变量组选择。本研究提出Group Logarithm模型,该模型能同时进行变量组选择和组内的变量选择,并利用局部坐标下降算法求解Group Logarithm模型。最后,通过实验说明了该模型具有更优越的预测准确性和变量选择稀疏性。

An Intelligent System for Analysing Manas Prakrti in Human Resource Management

Human resource management is said to be the importance of spiritual, ethical, and human values that condition human behaviour. The immediate problem that it poses for a full understanding of human functioning is that the inner subjective experiences of consciousness based on human resource management. Ayurveda occupies the heights of human psychological accomplishment and could usefully call upon the insights of any of these sources to aid in addressing the problematic nature of modern-day businesses and have significant bearing on human behaviour. Manas prakrti in Ayuverda contributes to the study of personality. Tamas-Rajas-Sattva temperamental groups give rise to the framework of Space-Time-Causation when evolution starts in association with Consciousness Principle in manas prakrti. In this paper I present a methodology to analyze Temperamental groups that are found in manas prakrti by using an intelligent system. This will guide understand, instrumental values, operating values, and weak values of employees in human resource management.

Algorithms for Increasing of the Effectiveness of the Making Decisions by Intelligent Fuzzy Systems

There are considered rule-based intelligent systems using fuzzy inference. Comparative analysis of different approaches and algorithms of making decisions on the base of fuzzy logic is given. Using of the parallel calculations can reduce the time of making decision in case of large-scale systems. Effectiveness of parallel calculations depends on the grouping of the rules and variables. Building of the graph of the dependence of the rules and the graph of dependence of the linguistic variables are suggested. On the base of the developed groups of rules and defuzzification of the linguistic variables we suggest to reduce the time of making decision and therefore to increase the effectiveness of the decision making with using of parallel calculations for each group.

元宇宙赋能公共图书馆无障碍服务:壁垒突破、体系构建与路径探究

公共图书馆无障碍服务致力于帮助残障人士等特殊群体享受公共文化服务、共享数字生活,是无障碍环境建设的一部分。元宇宙为公共图书馆无障碍服务提供了新思路,注入了新活力。文章通过阐述公共图书馆无障碍服务在互联网不同阶段的发展与变化,总结元宇宙赋能公共图书馆无障碍服务实现的壁垒突破,构建无障碍服务体系,探究推进路径。公共图书馆无障碍服务建设应多点突破,以用户需求为主导,提供更便捷的均等化服务,在元宇宙相关技术加持下弥合数字鸿沟,促进社会包容。

产业数字化背景下高等职业院校专业群建设模式的研究与实践——以福州职业技术学院为例

在产业数字化和智能化的发展背景下,以高职院校为研究对象,探讨了一种创新的专业群建设模式,旨在更好地满足数字经济时代对“传统技术+数字技术”的复合型技术技能人才的培养需求。该模式以“信息化”和“智能化”为引领,以支持产业数字化升级为目标,采用了一系列具体举措,包括专业群布局的优化、模块化“数字+”课程资源池的开发、共享型“两中心一基地”平台的建设,以及创新的校企合作保障机制。经实践该专业群建设模式能够有效地提升高等职业院校的人才培养质量,适应产业数字化发展的人才需求,可为职业教育领域专业数字化升级改造提供范式和参考。

群智创新时代下社区居家养老服务交互设计研究

目的解决目前养老中因服务组织参与度不高及智能交互产品利用率低下而导致的养老服务质量欠佳的问题。方法通过对当前社区居家养老服务现状进行分析,结合群智创新的发展及特点,分析养老服务设计的群智创新过程,提出了群智创新时代下基于用户的养老服务新组织,借助KANO模型原理对养老服务需求项目进行群体用户分析,并对分析数据结果进行优先顺序排序,获得老年用户群体对养老服务设计的真实需求情况。结果构建了以用户为中心的社区居家养老服务设计框架,并结合服务设计工具进行智能交互界面设计。结论对交互设计界面的测评显示,老年人对其满意度极高,该养老服务新模式有别于传统养老模式,顺应当今群智创新时代下大数据、互联网、云平台等科技的发展需求,在提高养老服务满意度的同时,使养老服务质量达到最优的效果。

人工智能课程群思政教学资源的挖掘、整合与融入

本文构建了“四层”人工智能课程群课程体系,对人工智能课程群的课程内容进行整合与重构;围绕课程群内各课程的教学目标和讲授内容,挖掘各课程思政元素,根据课程间的内容联系和逻辑关系,将思政元素整合为爱国主义和科技兴国、科学思维和工匠精神、创新开放和工程思维、科学伦理和职业道德等四类,并有机融入课程教学,形成界限分明、互为补充、各具特色的思政课程体系;通过课程考核评价机制验证人工智能课程群的思政教学成效。实践结果表明,该课程群思政教学有助于实现价值塑造、能力培养和知识传播的课程目标。

基于数智化视角的企业集团智慧型司库建设探究

随着数字经济的快速发展,企业集团需要加快数智化转型,作为集团运营管理重要载体的司库也需要相应转型。为满足司库数智化转型的三个基本要求。首先,需从司库的操作运营层、资源管控层、决策分析层等三个层级着手创新设计司库数智化转型的功能架构。其次,为支撑该功能架构,需从先进性、集成性、安全性、可拓展性等四个方面着手创新设计司库数智化转型的技术机构。最后,为确保建成智慧型司库,需从机制健全、过程管控、标准优化、数据治理等四个关键环节发力提供坚强保障举措。

城市道路网联混驾车辆分阶段动态轨迹控制方法

随着城市的进步和不断发展,智能驾驶车辆逐渐代替路段中的部分人工驾驶车辆,但在未来较长时间内人工驾驶车辆并不会被完全取代,此时出现网联车与人工驾驶车辆的混驾环境,即目前以及未来时间内我们面临的驾驶环境。网联车与人工驾驶车辆驾驶行为在路段内相互干扰,造成混合车流行驶效率低下。为减弱2种车辆间的相互作用,提出一种分离混驾环境下网联车和人工驾驶车辆的分阶段动态车道引导算法(dynamic lane guidance algorithm for separating CAVs and HDVs in mixed traffic environment,SCHME)。通过该算法分离在交叉口上游路段的混合流车辆集合,调整智能驾驶车辆的行驶路线并进行实时动态更新,在满足运动学约束收敛的条件下,人工驾驶车辆根据网联车的动态路线进行相应调整,实现在每辆车广义安全损失成本最小的情况下提高路段内混驾环境下车辆运行效率。通过MATLAB模拟车辆在进入交叉口前的车辆运行状态,结果表明,SCHME算法可在广义安全损失成本最小的情况下提高路段内平均车辆通行效率(17.29%),同时当车辆优化数组越大,车辆集合距离交叉口越远时,智能驾驶车辆渗透率越低,每辆车的道路广义安全损失成本越低。

基于卷积神经网络的“舌边白涎”舌象识别研究

目的通过机器学习分析“舌边白涎”舌象特性,对舌象进行局部特征识别研究,探讨卷积神经网络算法在舌象识别应用中的性能。方法使用Python进行图像预处理,搭建用于舌象识别的视觉几何组16层(visual geometry group 16,VGG16)卷积神经网络模型,分析其对“舌边白涎”舌象鉴别分析的效果,并结合热力图分析“舌边白涎”典型舌象表现。结果基于PyTorch框架,进行卷积神经网络的舌象鉴别研究,VGG16及残差网络50层(residual network 50,ResNet50)模型验证准确率均较高,达到80%以上,且ResNet50模型优于VGG16模型,可为舌象识别提供一定参考。基于加权梯度类激活映射(gradient-weighted class activation mapping,Grad-CAM)技术,通过舌苔舌色差异分布的网络可视化,有助于直观进行模型评估分析。结论基于卷积神经网络模型对舌象数据库进行分析,实现“舌边白涎”舌象识别,有助于临床诊疗的客观化辅助分析,为舌诊智能化发展提供一定借鉴。

1ZL-7.2型联合整地机的研制

整地作业可将犁耕后的土壤进行碎土、平整,为播种环节创造良好的作业条件,联合整地机在新疆已被广泛应用。近年来大中马力拖拉机保有量逐年增加,为提高整地作业幅宽和效率,研制了一款与大马力拖拉机相配套的联合作业机,开发了新型合金材料的耐磨耙片。作业幅宽为7.2 m,机架可以进行折叠便于运输。田间试验表明,该型机具作业效果良好,故障率低,操作简单、方便。