基于微服务的石油大数据挖掘平台

为推进大数据技术在油田领域的快速融合和应用，提出一种覆盖大数据处理整个生命周期的多功能大数据处理平台。平台融合各类大数据分析框架和机器学习框架，设计面向油田领域，能够支持实时和离线处理的数据挖掘功能。基于Docker容器封装各类计算框架和算法服务，并基于Kubernetes框架完成容器的编排与调度。在系统的架构方式上采用基于微服务的架构方式，将不同技术栈的应用独立分解为单个服务模块，以此来保证业务系统服务的可靠性、可扩展性。这使得企业数据分析人员能够专注于业务数据分析问题，而不必花费大量时间学习框架部署和其他大型数据挖掘技术细节。     

Mobile Social Networks and Social Practice: A Case Study of Dodgeball

A mobile social network system (MSNS) allows groups of friends to be accessed and engaged with from one's mobile phone. Dodgeball is a MSNS that seeks to facilitate social connection and coordination among friends in urban public spaces. Based on a year-long qualitative field study, this article reports on the social and behavioral norms of Dodgeball use. A comparison between social network sites and Dodgeball highlights some of the communicative differences of mobile technology and the Internet. The findings of the study suggest that Dodgeball use can influence the way that informants experience public space and social relations therein. At times Dodgeball can facilitate the creation of third spaces, which are dynamic and itinerant forms of "third places." Additionally, exchanging messages through Dodgeball can lead to social molecularization, whereby active Dodgeball members experience and move through the city in a collective manner.     

山东省采供血管理网络平台的建设与应用

叙述了山东省采供血系统如何利用先进互联网技术组建省内血液数据交换及协同工作平台,将山东省卫生厅、采供血机构及医院临床进行联网协同工作管理,并实现了全省血液信息的共享、交换、控制和统计分析、数据存储采用等功能。     

基于北斗的城市垃圾清运系统

为建设更美好的市容市貌, 降低运输车辆的空车率, 实现源头追溯与全流程透明化管理, 结合目前通用的软件开发方式与数据库技术, 给出了以智能化, 绿色为主的城市垃圾清运系统. 该系统以北斗定位数据为基础, 辅助以高德开放平台来进行设计开发. 系统的开发采用基于PHP语言的ThinkPHP框架以及B/S架构设计模式, 客户端采用Ajax和Web技术等方式实现数据的传输和展现. 该系统旨在为用户提供车辆实时位置查询、车辆历史轨迹查询、用户管理、统计分析等服务. 对于车辆运输过程中的整个轨迹数据, 系统采用了北斗系列来进行数据采集, 更有效地维护了信息和技术的安全. 后期还可结合机器学习等技术来对司机的驾驶行为, 车辆的健康状况进行相应分析. 通过北斗定位数据与互联网技术的结合, 该系统可有效地对车辆进行管理.     

Exploring social entrepreneurship education from a Web-based pedagogical perspective

As Internet has evolved itself as a powerful media for communication, and with the proliferation of Internet contents and survey methodologies, Internet-based researches such as Web-based surveys are common today. The World-Wide Web presents researchers with a powerful tool for the collection of data and the Web-based survey provided us with an efficient and valid method to code the data compared with costs associated with conventional surveying methods. Whereas many research studies use quantitative methodology for Web-based survey; this study employed a Web-based content analysis method to the theme how social entrepreneurship was taught in business school. On the basis of the Beyond Grey Pinstripes (BGP) Global 100 List: 2009–2010 of business schools, with an emphasis on environmental, social, and ethical complexities, we analyzed the contents of social entrepreneurship education, teaching methods, professional specialties of the teachers, and grading of the curricula. The results show that the courses offered by most of these business schools had the required social entrepreneurship characteristics. The arrangement of their programs and their teaching methods, which followed the principle of learning by doing, not only enabled the students to balance theory and practice, but also supported the students in creating social enterprises.     

基于Web2.0社会性软件的个人学习环境的探究

Web2.0这一互联网新一代模式以其个性化、共享性、开放性等特点为传统网络信息管理提供了一种全新的解决方法。而个人学习环境是自由的、分布的、以网络为基础的工具的集合,以blog为聚焦点,通过RSS订阅器整合内容形成的一个环境,更多的是关于社会性软件的应用。通过网络以及web2.0社会性软件构建一个较全面的个人学习环境,使学习者以个人主导者的身份来管理自己的学习,对学习的管理从教育机构转移到学习者自身,不仅实现内容和知识的简单转移,更演化到了内容和知识的创造与产出。     

食源性疾病事件智能探测与预警平台

食源性疾病由来已久,每年都会造成巨大的社会经济损失.人工智能技术给食源性疾病事件的探测和预警带来了新的方法.该文基于互联网大数据开发了食源性疾病事件智能探测与预警平台,该平台面向食源性疾病事件的数据获取、数据分析以及可视化展示的全过程,通过D-M-V分层模型以及模块化开发集成了多种模块.该平台主要解决了食源性疾病事件的数据获取、数据融合、事件探测、风险预测和可视化等问题,该平台能够自动从互联网中采集社交媒体、社会经济等数据;根据数据的时空坐标对多源异构数据进行高效融合;从社交媒体数据中探测出食源性疾病事件并推断其关键信息;利用多源数据对食源性疾病风险进行预测;提供高效的可视化方法和交互手段.该文通过2018年北京市食源性疾病数据作为示例验证平台功能.     

基于数据可视化的开放式虚拟教学平台的研究

简要介绍在Internet上建立的基于数据可视化的开放式虚拟教学平台模型,可通过收集网上的学习资源,并利用可视化工具将抽象的知识转化为生动形象的二雏图形和三维模型,以增添学习的乐趣,激发学生的学习积极性和主动性.     

基于Web的课程考试与实施系统技术探讨

介绍采用基于Web方式开发应用的课程考试平台系统，利用JSP的3层B／S结构技术，利用大型数据库及前端开发工具，充分发挥网络优势，设计并实现了一个较为完整和通用的网络考试平台技术系统。在此平台基础上，根据实际课程的特点和需要，可以灵活方便地进行二次开发，以实现对应的无纸化考试。     

互联网免费学习资源的收集与共享平台研究

对互联网上免费学习资源进行研究,并在校内搭建一个互联网免费学习资源的收集和共享平台,主要实现学习资源上传、教学视频实时点播、校内FTP资源共享、免费资源快速定位、教学软件下载等功能模块,为教师备课、学生自主学习提供免费资源,从而提高学生的学习效率。     

An integrated architecture for future studies in data processing for smart cities

Data processing for Smart Cities become more challenging, facing with different handling steps: data collection from different heterogeneous sources, processing sometimes in real-time and then delivered to high level services or applications used in Smart Cities. Applications used for intelligent transportation systems, crowd management, water resources management, noise and air pollution management, require different data processing techniques. The main subject of this paper is to propose an architecture for data processing in Smart Cities. The architecture is oriented on the flow of data from the source to the end user. We describe seven steps of data processing: collection of data from heterogeneous sources, data normalization, data brokering, data storage, data analysis, data visualization and decision support systems. We consider two case studies on crowd management in smart cities and on Intelligent Transportation Systems (ITS) and we provide experimental highlights.     

The orchestration of Machine Learning frameworks with data streams and GPU acceleration in Kafka-ML: A deep-learning performance comparative

Machine Learning (ML) applications need large volumes of data to train their models so that they can make high-quality predictions. Given digital revolution enablers such as the Internet of Things (IoT) and the Industry 4.0, this information is generated in large quantities in terms of continuous data streams and not in terms of static datasets as it is the case with most AI (Artificial Intelligence) frameworks. Kafka-ML is a novel open-source framework that allows the complete management of ML/AI pipelines through data streams. In this article, we present new features for the Kafka-ML framework, such as the support for the well-known ML/AI framework PyTorch, as well as for GPU acceleration at different points along the pipeline. This pipeline will be described by taking a real Industry 4.0 use case in the Petrochemical Industry. Finally, a comprehensive evaluation with state-of-the-art deep learning models will be carried out to demonstrate the feasibility of the platform.     

互联网个人信息挖掘模型设计

互联网个人信息挖掘技术是指综合利用搜索引擎、博客、网络社交平台等一系列互联网公开资源挖掘某个人物的个人信息。通过从互联网上海量信息中提取线索,寻找关联,最终获取所需信息。本文设计了一种互联网个人信息挖掘模型并详细介绍了其工作原理与应用,利用该模型所提供的方法可以有效进行互联网个人信息挖掘。     

Policy making for broadband adoption and usage in Chile through machine learning

For developing countries, such as Chile, we study the influential factors for adoption and usage of broadband services. In particular, subsidies on the broadband price are analyzed to see if this initiative has a significant effect in the broadband penetration. To carry out this study, machine learning techniques are used to identify different household profiles using the data obtained from a survey on access, use, and users of broadband Internet from Chile. Different policies are proposed for each group found, which were then evaluated empirically through Bayesian networks. Results show that an unconditional subsidy for the Internet price does not seem to be very appropriate for everyone since it is only significant for some households groups. The evaluation using Bayesian networks showed that other polices should be considered as well such as the incorporation of computers, Internet applications development, and digital literacy training.     

A social investing approach for portfolio recommendation

Presently, people use social media at a greater rate to share their personal investment experiences. This plentiful user-generated data source has been promisingly used by investors for portfolio creation. A new type of investing platform that allows investors to copy the portfolios of experienced investors has grown dramatically. In this research, we propose a collective intelligence mechanism that can extract and consolidate the opinions expressed over the social investing platform and generate appropriate portfolios by analyzing other investors’ knowledge, authority, and opinions toward the investment target. The experimental results obtained based on the social investing platform eToro.com reveal that the portfolio recommended by the proposed mechanism outperforms the market index and other benchmark approaches in various financial performance aspects.     

Toward a model for the study of children’s informal Internet use

Throughout history, the development and widespread use of new technologies has impacted human cognition and social structures. By integrating a range of cognitive and socio-cultural theories we are better able to understand the impact of technological tools, such as the Internet, on children in the context of their local and global communities. An integrated theoretical approach enables us to more comprehensively ascertain the potential of the Internet to significantly impact children’s cognitive processes and the larger social implications of this global phenomenon. This paper presents a small-scale exploratory study that, through the development of an Internet-mediated learning model, examines the skills and characteristics of young, competent Internet-users engaged in informal Internet activities. At present, there is much conjecture on the ways in which the Internet may affect learning and this paper describes an approach to research that could inform future data collection procedures and analysis in empirical studies.     

Interactive processes and learning attitudes in a web-based problem-based learning (PBL) platform

This paper discusses the steps taken to set up a digital logic course problem through a problem-based learning (PBL) constructivist approach. PBL is the learning which results from the process of working toward the understanding and resolution of a problem. The purpose of this study was to develop and implement problem-based learning in a digital logic course in a senior vocational industrial high school. Data collection included content analysis and a questionnaire survey. Content analysis was used to evaluate the students’ discussion messages, quality of dialogue, and the level of problem-solving activities. A survey was then administered to examine the students’ learning attitudes and perceptions toward this platform as a possible tool for PBL learning. Researchers found “Peer-responses” category is the most messages; the contents of messages focus on “General explanation” and “Reaction”; the level results of all groups’ problem-solving are similar; the index of the “Interaction” satisfaction level is the highest in PBL activity. Finally, some research suggestions were also proposed.     

Social skills as predictors of communication,performance and quality of collaboration in project‐based learning

The assumption that social skills are necessary ingredients of collaborative learning is well established but rarely empirically tested. In addition, most theories on collaborative learning focus on social skills only at the personal level, while the social skill configurations within a learning group might be of equal importance. Using the integrative framework, this study investigates which social skills at the personal level and at the group level are predictive of task‐related e‐mail communication, satisfaction with performance and perceived quality of collaboration. Data collection took place in a technology‐enhanced long‐term project‐based learning setting for pre‐service teachers. For data collection, two questionnaires were used, one at the beginning and one at the end of the learning cycle which lasted 3 months. During the project phase, the e‐mail communication between group members was captured as well. The investigation of 60 project groups (N = 155 for the questionnaires; group size: two or three students) and 33 groups for the e‐mail communication (N = 83) revealed that personal social skills played only a minor role compared to group level configurations of social skills in predicting satisfaction with performance, perceived quality of collaboration and communication behaviour. Members from groups that showed a high and/or homogeneous configuration of specific social skills (e.g., cooperation/compromising, leadership) usually were more satisfied and saw their group as more efficient than members from groups with a low and/or heterogeneous configuration of skills.     

基于微信企业号的干部学习平台

针对干部在线教育信息化水平偏低和已有APP客户端干部学习平台使用效率低的现状,设计并实现了一种基于微信企业号的干部学习平台,并以重庆干部网络学院官方微信学习平台为例,对平台的可行性进行了验证.该平台应用微信企业号提供的接口实现了与PC平台、APP客户端的数据对接与同步,采用PHP、HTML5、JSON等Web开发技术实现了个人中心、每日一课、电子书等功能.干部可以在社交网络环境中,通过信息交互完成在线学习并获取资讯与服务.为广大干部学习者提供了一种新的学习途径,提升了干部使用的便捷性,有效提高了学习效率.     

移动学习社群模式在中职电子商务 教学中的应用探索

“互联网+”时代的到来,特别是移动互联网的普及,移动社交网络的兴起,为教育信息化从“E-learning（数字 学习）”到“M-learning（移动学习）”的转型奠定了良好的基础。本文首先分析了“互联网+社交”背景下的移动学习的特点,然 后在此基础上利用蓝墨云班课、微信公众平台、微信群和QQ 群等构建移动学习社群平台,最后探究了该教学模式在实际教学 应用中的策略和措施,提出了开展移动学习社群教学的困境,以期为职业教育信息化教学提供参考和思路。