模块式墙体绿化技术

模块化墙体绿化具有系统化,速成景,易装卸等优点,日益受到建筑师的青睐。但国内的墙体绿化处于起步阶段,该文介绍三种国外较为成熟的模块式墙体绿化系统,对系统构造、基质选择、维护以及适用性进行了分析,为国内建筑师及园林设计师提供墙体绿化设计及构造设计参考。     

Efficiently using contextual influence to recommend new items to ephemeral groups

Group recommender systems suggest items to groups of users that want to utilize those items together. These systems can support several activities that can be performed together with other people and are typically social, like watching TV or going to the restaurant. In this paper we study ephemeral groups, i.e., groups constituted by users who are together for the first time, and for which therefore there is no history of past group activities.Recent works have studied ephemeral group recommendations proposing techniques that learn complex models of users and items. These techniques, however, are not appropriate to recommend items that are new in the system, while we propose a method able to deal with new items too. Specifically, our technique determines the preference of a group for a given item by combining the individual preferences of the group members on the basis of their contextual influence, the contextual influence representing the ability of an individual, in a given situation, to guide the group’s decision. Moreover, while many works on recommendations do not consider the problem of efficiently producing recommendation lists at runtime, in this paper we speed up the recommendation process by applying techniques conceived for the top-$K$ query processing problem. Finally, we present extensive experiments, evaluating: (i) the accuracy of the recommendations, using a real TV dataset containing a log of viewings performed by real groups, and (ii) the efficiency of the online recommendation task, exploiting also a bigger partially synthetic dataset.     

基于文化生态学的海岛人居环境建设研究——以舟山群岛为例

实现文化生态系统和人居环境系统的融合涉及到大量的工作。本课题研究的目的在于,从文化生态角度着手,解决舟山群岛新区建设给人居环境带来的破坏,实现人地关系的和谐发展。笔者在结合新区所处区位现状的基础上,充分利用文化生态以及人居环境方面的理论成果,从实用性科学角度出发,对舟山群岛城市建设的过去、现在和将来进行全面且细致的分析,以提高该地域人居环境整体质量。     

Current trends on ICT technologies for enterprise information systems

As business conditions change rapidly, the need for integrating business and technical systems calls for novel ICT frameworks and solutions to remain concurrent in highly competitive markets. A number of problems and issues arise in this regard. In this paper, four big challenges of enterprise information systems (EIS) are defined and discussed: (1) data value chain management; (2) context awareness; (3) usability, interaction and visualization; and (4) human learning and continuous education. Major contributions and research orientations of ICT technologies are elaborated based on selected key issues and lessons learned. First, the semantic mediator is proposed as a key enabler for dealing with semantic interoperability. Second, the context-aware infrastructures are proposed as a main solution for making efficient use of EIS to offer a high level of customization of delivered services and data. Third, the product avatar is proposed as a contribution to an evolutionary social, collaborative and product-centric and interaction metaphor with EIS. Fourth, human learning solutions are considered to develop individual competences in order to cope with new technological advances. The paper ends with a discussion on the impact of the proposed solutions on the economic and social landscape and proposes a set of recommendations as a perspective towards next generation of information systems.     

思考设计:历史、进步与批评

本文通过诸多设计案例展示"设计"在表现形式、工程学,以及人与物间的交流等方面的探索,并指出设计史研究中的局限性。作者将这些局限当成是一种激励,以促进读者思考造成这些局限的原因,寻找克服的方法以推动设计史研究的进步。文章将史学的视角带入设计的研究,提供设计发展背后的经济、政治和社会文本,向读者展示一个拓展的设计世界。     

Intelligent services for Big Data science

Cities are areas where Big Data is having a real impact. Town planners and administration bodies just need the right tools at their fingertips to consume all the data points that a town or city generates and then be able to turn that into actions that improve peoples’ lives. In this case, Big Data is definitely a phenomenon that has a direct impact on the quality of life for those of us that choose to live in a town or city. Smart Cities of tomorrow will rely not only on sensors within the city infrastructure, but also on a large number of devices that will willingly sense and integrate their data into technological platforms used for introspection into the habits and situations of individuals and city-large communities. Predictions say that cities will generate over 4.1 terabytes per day per square kilometer of urbanized land area by 2016. Handling efficiently such amounts of data is already a challenge. In this paper we present our solutions designed to support next-generation Big Data applications. We first present CAPIM, a platform designed to automate the process of collecting and aggregating context information on a large scale. It integrates services designed to collect context data (location, user’s profile and characteristics, as well as the environment). Later on, we present a concrete implementation of an Intelligent Transportation System designed on top of CAPIM. The application is designed to assist users and city officials better understand traffic problems in large cities. Finally, we present a solution to handle efficient storage of context data on a large scale. The combination of these services provides support for intelligent Smart City applications, for actively and autonomously adaptation and smart provision of services and content, using the advantages of contextual information.     

An extended attribute based access control model with trust and privacy: Application to a collaborative crisis management system

Many efforts in the area of computer security have been drawn to attribute-based access control (ABAC). Compared to other adopted models, ABAC provides more granularity, scalability, and flexibility. This makes it a valuable access control system candidate for securing platforms and environments used for coordination and cooperation among organizations and communities, especially over open networks such as the Internet. On the other hand, the basic ABAC model lacks provisions for context, trust and privacy issues, all of which are becoming increasingly critical, particularly in high performance distributed collaboration environments. This paper presents an extended access control model based on attributes associated with objects and subjects. It incorporates trust and privacy issues in order to make access control decisions sensitive to the cross-organizational collaboration context. Several aspects of the proposed model are implemented and illustrated by a case study that shows realistic ABAC policies in the domain of distributed multiple organizations crisis management systems. Furthermore, the paper shows a collaborative graphical tool that enables the actors in the emergency management system to make better decisions. The prototype shows how it guarantees the privacy of object’s attributes, taking into account the trust of the subjects. This tool incorporates a decision engine that relies on attribute based policies and dynamic trust and privacy evaluation. The resulting platform demonstrates the integration of the ABAC model, the evolving context, and the attributes of actors and resources.     

Enhancing clustering quality of geo-demographic analysis using context fuzzy clustering type-2 and particle swarm optimization

Geo-Demographic Analysis, which is one of the most interesting inter-disciplinary research topics between Geographic Information Systems and Data Mining, plays a very important role in policies decision, population migration and services distribution. Among some soft computing methods used for this problem, clustering is the most popular one because it has many advantages in comparison with the rests such as the fast processing time, the quality of results and the used memory space. Nonetheless, the state-of-the-art clustering algorithm namely FGWC has low clustering quality since it was constructed on the basis of traditional fuzzy sets. In this paper, we will present a novel interval type-2 fuzzy clustering algorithm deployed in an extension of the traditional fuzzy sets namely Interval Type-2 Fuzzy Sets to enhance the clustering quality of FGWC. Some additional techniques such as the interval context variable, Particle Swarm Optimization and the parallel computing are attached to speed up the algorithm. The experimental evaluation through various case studies shows that the proposed method obtains better clustering quality than some best-known ones.     

Technical Note: Method for objective assessment of physical work load at the workplace

This paper presents a method for objective assessment of physical work load at the workplace. The method is based on the DynaPort ADL Monitor. Using accelerometry, this monitor enables the assessment of gross motor activity as it occurs during the activities of daily living (ADL). A case study is conducted to explore the usefulness of the monitor in support of occupational research. The focus is on the cause and reduction of mechanical low back pain (LBP). A patient suffering from mechanical LBP participated in the study. He worked as messenger in contrast with his usual occupation. The patient was examined in both occupations using the monitor. The ADL profiles indicated that the messenger job was more likely to cause LBP than the other occupation of a mechanic.