Knowledge management and communication in Brazilian agricultural research: An integrated procedural approach

The great contemporary organizational challenge for enterprises is to create a conceptual and methodological framework allows the management of knowledge by means of networks designed for social interaction. This statement is based on the premise that the competitive drive and sustainable success of the company depend on the introduction of new forms of production innovative processes, which can only be ensured through integrated approaches to knowledge management and the incorporation information technologies (IT). This is a reality that has already been accepted by the Brazilian Agricultural Research Corporation (Embrapa, its acronym in Portuguese), a Brazilian research, development, and innovation (RD&I) institution supporting agricultural sector. For some years now, Embrapa has been incorporating what it has learned about knowledge management into its strategic planning process. In this paper, we present a new approach to managing knowledge and information, and we analyze the need for research institutions to administer the knowledge they produce through an RD&I management model based multi- and inter-disciplinary teams, and multi-institutional research networks.     

无穷区间上S分布时滞静态递归神经网络模型的全局周期吸引子

研究了无穷区间上S分布时滞静态递归神经网络模型的全局吸引子,并给出了有实用性的判据和实例.     

The importance of networks for newly qualified teachers in upper secondary education

Background and purpose:?The interest in raising the competence of teachers through networks and network activities is increasing. This article is based on the voices of four newly qualified teachers who give us the opportunity to listen to experiences in authentic surroundings. The purpose of this article is to gain better insight into the type of networks newly qualified teachers maintain, develop and create to develop as teachers. The research question is: What is the importance of networks for the professional development of newly qualified teachers in upper secondary education?

Main argument:?The main finding of the article, based on in-depth interviews with four newly qualified teachers, is that being acknowledged by colleagues is decisive for professional development. Furthermore, the school’s programme of meetings to some extent contributes to developing the respect and trust of the newly qualified teachers, who also need to find time and opportunities for reflection in personal networks outside school. The relational and emotional aspects of the teaching profession produce a need for guidance processes where the ethical dilemmas of the profession can be raised. When these dilemmas arise, the newly qualified teachers actively look outside school to grasp opportunities for professional development. The teachers appear to be very active in their own professional development, and they have ambitions to develop as teachers for the benefit of the pupils and the school.

Conclusions:?Systematic guidance is highlighted as fundamental for these teachers’ learning.     

压力流雨水排水系统在实际工程中的应用

结合春兰电子商务有限公司物流配送中心厂房，对重力流和压力流雨水排水系统在工程中的应用进行分析比较。介绍了适用于大屋面雨水排放的压力流雨水排水系统中雨水斗和管道的安装方法。     

矿井自动排水系统综述

叙述矿井自动排水系统的组成和工作方式,介绍了矿井自动排水系统的分类和某些系统硬件的安装及作用,讲述大多数矿井自动排水系统具备的特点,最后分析系统中PCL的可靠性及其解决办法。     

无线Ad Hoc网络中一种网络无关的P2P流媒体优化传输方案

根据无线Ad Hoc网络环境下P2P流媒体数据传输的特点,提出一种工作在P2P数据拓扑层面的,不依赖于底层物理网络的节点配置和特定的路由算法的优化传输方案.在发送数据时,节点结合应用层视频分片的重要性和网络状况动态地调整传输层参数,从而减小重要数据的传输延时和播放超时的概率.仿真结果验证了本方案对于改善服务质量和减小控制信令开销的有效性.     

三网融合背景下华数传媒集团的跨界探索及启示

杭州华数传媒在数字电视发展伊始,就将数字电视定位为家庭信息化终端和城市信息化综合平台进行跨界发展,从而使数字电视获得了较为广阔的可持续发展空间。在三网融合的背景下,华数传媒的跨界探索对其毳数字电视运管企业而吉,具有重要的启示。     

Looking deep in the eyes: Investigating interpretation methods for neural models on reading tasks using human eye-movement behaviour

This paper provides the first broad overview of the relation between different interpretation methods and human eye-movement behaviour across different tasks and architectures. The interpretation methods of neural networks provide the information the machine considers important, while the human eye-gaze has been believed to be a proxy of the human cognitive process. Thus, comparing them explains machine behaviour in terms of human behaviour, leading to improvement in machine performance through minimising their difference. We consider three types of natural language processing (NLP) tasks: sentiment analysis, relation classification and question answering, and four interpretation methods based on: simple gradient, integrated gradient, input-perturbation and attention, and three architectures: LSTM, CNN and Transformer. We leverage two corpora annotated with eye-gaze information: the Zuco dataset and the MQA-RC dataset. This research sets up two research questions. First, we investigate whether the saliency (importance) of input-words conform with those from human eye-gaze features. To this end, we compute a saliency distance (SD) between input words (by an interpretation method) and an eye-gaze feature. SD is defined as the KL-divergence between the saliency distribution over input words and an eye-gaze feature. We found that the SD scores vary depending on the combinations of tasks, interpretation methods and architectures. Second, we investigate whether the models with good saliency conformity to human eye-gaze behaviour have better prediction performances. To this end, we propose a novel evaluation device called “SD-performance curve” (SDPC) which represents the cumulative model performance against the SD scores. SDPC enables us to analyse the underlying phenomena that were overlooked using only the macroscopic metrics, such as average SD scores and rank correlations, that are typically used in the past studies. We observe that the impact of good saliency conformity between humans and machines on task performance varies among the combinations of tasks, interpretation methods and architectures. Our findings should be considered when introducing eye-gaze information for model training to improve the model performance.     

Explaining attendance through the brand community triad: Integrating network theory and team identification

In this study, the authors empirically test a model of sport behaviour that integrates both team identification and a network theory approach to understand attendance at intercollegiate ice hockey games. Grounded within the brand community triad, ego network data were collected among attendees to measure the fan-to-fan connections that constitute the horizontal relationships of brand community participants. Additionally, a multidimensional team identification measure was used to illustrate the vertical relationship between individual and team. Both measures were included in a structural equation model to test how both fan-to-fan and fan-team relationships explain attendance. The results from the model support the salience of both dimensions of the brand community triad, suggesting that understanding sport fan behaviour necessitates including both psychological and structural elements of behaviour. Future suggestions for extending the study of sport fans through structural networks are discussed.     

基于用户行为感知的移动社交网络信息服务持续使用意愿研究

[目的/意义]本文以用户行为感知视角，研究影响移动社交网络主导型用户与浏览型用户持续使用的因素，为移动社交网络信息服务提供理论基础，并为移动社交网络提供商提出参考与应用借鉴。[方法/过程]分析移动社交网络主导型用户与浏览型用户持续使用意愿影响因素，引入相关变量，构建了基于用户行为感知的移动社交网络信息服务持续使用意愿模型并提出假设，最后通过结构方程模型进行实证分析。[结果/结论]感知有用性、感知易用性、感知娱乐、感知质量等因素均显著影响主导型及浏览型两类用户；服务质量、感知风险、知识获取、个人创新、社会认可、感知信任、感知转换成本等因素对两类用户有不同程度的影响。