A new humanitarian relief logistic network for multi-objective optimization under stochastic programming

Millions of affected people and thousands of victims are consequences of earthquakes, every year. Therefore, it is necessary to prepare a proper preparedness and response planning. The objectives of this paper are i) minimizing the expected value of the total costs of relief supply chain, ii) minimizing the maximum number of unsatisfied demands for relief staff and iii) minimizing the total probability of unsuccessful evacuation in routes. In this paper, a scenario based stochastic multi-objective location-allocation-routing model is proposed for a real humanitarian relief logistics problem which focused on both pre- and post-disaster situations in presence of uncertainty. To cope with demand uncertainty, a simulation approach is used. The proposed model integrates these two phases simultaneously. Then, both strategic and operational decisions (pre-disaster and post-disaster), fairness in the evacuation, and relief item distribution including commodities and relief workers, victim evacuation including injured people, corpses and homeless people are also considered simultaneously in this paper. The presented model is solved utilizing the Epsilon-constraint method for small- and medium-scale problems and using three metaheuristic algorithms for the large-scale problem (case study). Empirical results illustrate that the model can be used to locate the shelters and relief distribution centers, determine appropriate routes and allocate resources in uncertain and real-life disaster situations.

     

A model for evacuation risk assessment with consideration of pre- and post-disaster factors

In urban areas, the occurrence of disasters can cause extensive damage to human society. For this reason, evacuation, regarded as a critical course of action to relocate people and property, helps to alleviate loss of life and property to a great extent. Risk associated with evacuation is an abstract concept that cannot be easily conceptualized. This paper develops a model for assessing and visualizing the risks associated with the evacuation process in response to potential catastrophes. Understanding of evacuation risk, the potential for losing transport connections and the difficulty of transferring rescue resources, was previously limited by considering pre-disaster factors only. This study mitigates such limitation by extending previous research to include the contingent post-disaster factors that have received scant attention to date. Two contingent post-disaster factors: the spatial impact of the disaster and the potential for traffic congestion caused by the evacuee routing behaviors, are discussed in detail and integrated into the model along with other pre-disaster factors. A case study on the transportation network of Beijing, China is used to demonstrate the value of the model. This paper asserts that the notion of evacuation risk is not a static evaluation of such factors as road vulnerability; rather it involves a dynamic process where contingent factors associated with disastrous events play a role. This model can help city emergency planners to identify urban infrastructures that may hinder an efficient evacuation process because of their deficient configuration.     

Community detection in Social Media

The proposed survey discusses the topic of community detection in the context of Social Media. Community detection constitutes a significant tool for the analysis of complex networks by enabling the study of mesoscopic structures that are often associated with organizational and functional characteristics of the underlying networks. Community detection has proven to be valuable in a series of domains, e.g. biology, social sciences, bibliometrics. However, despite the unprecedented scale, complexity and the dynamic nature of the networks derived from Social Media data, there has only been limited discussion of community detection in this context. More specifically, there is hardly any discussion on the performance characteristics of community detection methods as well as the exploitation of their results in the context of real-world web mining and information retrieval scenarios. To this end, this survey first frames the concept of community and the problem of community detection in the context of Social Media, and provides a compact classification of existing algorithms based on their methodological principles. The survey places special emphasis on the performance of existing methods in terms of computational complexity and memory requirements. It presents both a theoretical and an experimental comparative discussion of several popular methods. In addition, it discusses the possibility for incremental application of the methods and proposes five strategies for scaling community detection to real-world networks of huge scales. Finally, the survey deals with the interpretation and exploitation of community detection results in the context of intelligent web applications and services.     

Impacts of the Wenchuan Earthquake on the Chaping River upstream channel change

The Wenchuan Earthquake, measuring magnitude 8.0 on the Richter scale, occurred on 12 May 2008 in Sichuan, southwest China and caused over 87 000 casualties. Geological disasters such as debris flows and landslides caused by the Wenchuan Earthquake were severe. Several high-risk dammed lakes formed in the Chaping River basin of An’xian County, Sichuan, China, which is located in the earthquake zone, caused great changes in river morphology and brought great danger to the people and properties in the river downstream. Channel change information from different periods was important to risk relief of dammed lakes and assessment of losses. A Satellite Pour l’Observation de la Terre 5 (SPOT 5) fused image of 10 November 2006 with 2.50 m spatial resolution, and unmanned aerial vehicle (UAV) images of 19 May 2008 and 23 December 2008 with 0.32 and 0.33 m spatial resolution, respectively, were applied to derive channel information in the Chaping River upstream from three periods (pre-disaster, during the disaster and post-disaster) using an object-oriented classification method with an edge-based segmentation algorithm and a support vector machine (SVM) classifier. Geological landslides and dammed lakes from different periods were analysed. Based on the channel information from different periods, channel changes were determined, and impacts of the earthquake on channel area, channel width, river morphology, and so on were discussed.     

Sentiment Analysis System in Big Data Environment

Nowadays, Big Data, a large volume of both structured and unstructured data, is generated from Social Media. Social Media are powerful marketing tools and social big data can offer the business insights. The major challenge facing social big data is attaining efficient techniques to collect a large volume of social data and extract insights from the huge amount of collected data. Sentiment Analysis of social big data can provide business insights by extracting the public opinions. The traditional analytic platforms need to be scaled up for analyzing a large volume of social big data. Social data are by nature shorter and generally not constructed with proper grammatical rules and hence difficult to achieve high reliable result in Sentiment Analysis. Acquiring effective training data is a challenge, although learning based approaches are good for sentiment classification. Manual Labeling for training data is time and labor consuming. In this paper, Sentiment Analysis system on Big Data Analytics platform is proposed to provide valuable information by analyzing large scale social data in an efficient and timely manner since they have been implemented using a MapReduce framework and a Hadoop distributed storage (HDFS). The proposed Sentiment Analysis system consists of four modules: data collection, data cleaning and preprocessing, class labeling and sentiment classification. The system enables high-level performance of sentiment classification while taking advantage of combining lexicon-based classifier’s effortless setup process and learning based classifier. Twitter stream data is used for system evaluation as the Twitter is widespread Social Media and a good source of information in the sense of snapshots of moods and feelings as well as up-to-date events. The evaluation results show that this system achieve a promising accuracy by 84.2%. Moreover, this system is able to scale up to analyze the large scale data by decreasing the processing time when adding more nodes in the cluster.     

Coordinating efficiency and equity in disaster relief logistics via information updates

This paper addresses a multi-supplier, multi-affected area, multi-relief, and multi-vehicle relief allocation problem in disaster relief logistics. A multi-objective optimisation model based on disaster scenario information updates is proposed in an attempt to coordinate efficiency and equity through timely and appropriate decisions regarding issues such as vehicle routing and relief allocation. An optimal stopping rule is also proposed to determine the optimum period of delay before responding to disaster, because decision making requires accurate disaster information. The main contribution of this paper is solving relief allocation problem in a novel way by correlating operational research with statistical decision making and Bayesian sequential analysis. Finally, a case is presented based on the post-disaster rescue in Eastern China after supertyphoon Saomai to test the applicability and show the potential advantages of the proposed model.     

Banking in the Internet and mobile era

Large parts of today's banking business are based on the application of information technology (IT). This applies to advisory at the customer frontend to and internal operations in banks to the electronic stock exchanges and transaction networks. To position the five contributions in the special issue on ??Banking in the Internet and Mobile Era??, this editorial suggests a framework that structures the application areas of IT in the banking industry. It recognizes IT as the enabler for all four tiers of the banking value chain and highlights the specific role of the regulatory environment in this industry. The special issue emphasizes the transformation of the banking industry towards more customer-orientation as well as the role of Internet and mobile technologies to change established channels and banking services.     

Design and CAD for Nanotechnologies

Recent innovations in nanoscale devices offer the potential for greater information density and system functionality. However, such devices present several new challenges. Design methodologies and tools have obtained a tremendous degree of sophistication and predictive value, and there are advantages in using the power of these tools to define a context for evaluating next-generation nanoelectronic technologies. Without a common context of systems evaluation, it will be difficult to make early viability assessments of new nanoelectronic-device approaches, nor will it be possible to strategically guide the development of these new technologies. This issue of IEEE Design & Test offers a special section on such topics. In addition, this issue presents the first in a series of tutorial articles derived from presentations at Test Technology Educational Program (TTEP) conferences. Finally, there are five general-interest articles on a wide range of topics.     

A Stochastic Optimization Model to Reduce Expected Post-Disaster Response Time Through Pre-Disaster Investment Decisions

This paper seeks to enhance network survivability under a disaster and reduce the expected post-disaster response time for transportation networks through pre-disaster investment decisions. The planning focuses on determining the links of the network to strengthen through investment under two types of uncertainties: the disaster characteristics, and the surviving network under each disaster. A bi-level stochastic optimization model is proposed for this problem, in which link investment decisions are made at the upper level to enhance the network survivability subject to a budget constraint such that the expected post-disaster response time is minimized at the lower level. A two-stage heuristic algorithm is proposed to obtain effective solutions efficiently. The numerical experiments indicate that the proposed heuristic algorithm converges to a fixed point representing a feasible solution, within an acceptable tolerance level, of the bi-level stochastic optimization model which is an effective solution under disasters of moderate severity. Parametric and sensitivity analyses reinforce the need for a holistic approach that integrates multiple relevant considerations to determine the link investment decisions.     

Pre-disaster investment decisions for strengthening a highway network

We address a pre-disaster planning problem that seeks to strengthen a highway network whose links are subject to random failures due to a disaster. Each link may be either operational or non-functional after the disaster. The link failure probabilities are assumed to be known a priori, and investment decreases the likelihood of failure. The planning problem seeks connectivity for first responders between various origin–destination (O–D) pairs and hence focuses on uncapacitated road conditions. The decision-maker's goal is to select the links to invest in under a limited budget with the objective of maximizing the post-disaster connectivity and minimizing traversal costs between the origin and destination nodes. The problem is modeled as a two-stage stochastic program in which the investment decisions in the first stage alter the survival probabilities of the corresponding links. We restructure the objective function into a monotonic non-increasing multilinear function and show that using the first order terms of this function leads to a knapsack problem whose solution is a local optimum to the original problem. Numerical experiments on real-world data related to strengthening Istanbul's urban highway system against earthquake risk illustrate the tractability of the method and provide practical insights for decision-makers.     

位置大数据隐私保护研究综述

大数据时代移动通信和传感设备等位置感知技术的发展形成了位置大数据,为人们的生活、商业运作方法以及科学研究带来了巨大收益.由于位置大数据用途多样,内容交叉冗余,经典的基于“知情与同意”以及匿名的隐私保护方法不能全面地保护用户隐私.位置大数据的隐私保护技术度量用户的位置隐私,在信息论意义上保护用户的敏感信息.介绍了位置大数据的概念以及位置大数据的隐私威胁,总结了针对位置大数据隐私的统一的基于度量的攻击模型,对目前位置大数据隐私保护领域已有的研究成果进行了归纳.根据位置隐私的保护程度,可以把现有方法总结为基于启发式隐私度量、概率推测和隐私信息检索的位置大数据隐私保护技术.对各类位置隐私保护技术的基本原理、特点进行了阐述,并重点介绍了当前该领域的前沿问题：基于隐私信息检索的位置隐私保护技术.在对已有技术深入分析对比的基础上,指出了未来在位置大数据与非位置大数据相结合、用户背景知识不确定等情况下保护用户位置隐私的发展方向.     

智能标识卡在井矿人员定位系统中的应用

针对目前矿井下通信系统功能不完善、技术与实现复杂的现状,设计了一种基于多功能智能标识卡的井下人员定位系统。给出了设计方案和设备选型;设计了系统功能,包括数据采集与预警、人员定位跟踪、灾后救援功能、综合信息管理等。     

Informal learning in work environments: training with the Social Web in the workplace

The Internet and its increasing usage has changed informal learning in depth. This change has affected young and older adults in both the workplace and in higher education. But, in spite of this, formal and non-formal course-based approaches have not taken full advantage of these new informal learning scenarios and technologies. The Web 2.0 is a new way for people to communicate across the Internet. Communication is a means of transformation and knowledge exchange. These are the facts that cannot be obviated by the organisations in their training programmes and knowledge management. This special issue is devoted to investigating how informal learning changes or influences online information in Social Web and training strategies in institutions. In order to do so, five papers will present different approaches of informal learning in the workplace regarding Web 2.0 capabilities.     

基于3维模型的数字浮雕生成技术

目的 浮雕是雕塑艺术的一种,根据其空间结构和用途的不同分为高浮雕、浅浮雕和凹浮雕3类。随着数字化技术和3D打印技术的发展,数字化浮雕的生成技术已经成为近年来计算机图形学领域的研究热点之一,从3维模型生成浮雕以其真实自然的效果成为浮雕生成的主要方法之一。为了使即将进入该领域的学者尽快了解该方法的现状和发展趋势,本文对3种类型的浮雕生成技术进行了系统的综述。方法 介绍了3种类型的浮雕生成技术,着重比较分析了基于3维网格模型的数字浅浮雕生成过程中的关键技术,存在问题及解决方案。针对复杂3维网格模型在生成数字凹浮雕过程中存在的部分细节信息丢失、特征线类型体现形式不完善、线条与形体间的过渡尚未解决、生成浮雕效果不自然等具体问题,提出了适用于3维复杂网格模型生成数字凹浮雕的研究方案。同时,从角色动画序列出发,对最优浮雕的生成技术进行了探讨,探讨结合信息熵理论计算选择最佳动作及观察视角的场景,还原艺术家的创作过程,为适用于面向3维打印的用户浮雕产品定制服务提供了可行的解决方案。结果 基于3维模型的浮雕生成方法是生成数字浮雕的一种重要方法,如何通过压缩和细节保持相关算法得到效果自然的浮雕模型一直是研究者们研究的热点问题。结论 虽然由3维模型生成数字浮雕是一种行之有效的方法,但是仍存在细节信息丢失、线条过渡不自然、特征线类型不完善等几个值得继续研究的问题,另外一个值得研究的问题就是如何智能地从3维动画序列生成浮雕。     

Guest Editorial

The extreme high speed of change in the area of information technology creates a new demand for a process of continues learning and relearning in the workplaces but also among the public as a whole. There is need for a deeper crossdisciplinary and interdisciplinary understanding of the effects of this extreme demand for learning and relearning, both on us as individuals, on public and private organization and on the society as a whole. Information technology provides to some extent possible solutions to the problems it creates. Consequently, web based learning is also expanding with an accelerating speed. But this new form of learning is not to the same extent backed up by a fast growing research, in areas like on-the job-learning, workplace pedagogics, 'competence ergonomics', etc. But there are a number of very good exceptions like the Knowledge Media Institute of the Open University, and also a number of newly established facilities like the network university in the north of Sweden, the Mid Sweden University. In this special issue these types of problems are discussed, including those where the emphasis lies in creating rational and effective methods for web-based training and learning. The following was put forward in the invitation to a particular target group for this special issue.     

Editorial

Quantum technology is recognized as one of the most promising directions for our future technologies. By exploiting the unique features of quantum effects, emerging quantum technology is rapidly progressing around the world including quantum computation, quantum communication, quantum metrology and quantum simulation. The development of quantum control plays a grounding role in enabling the preservation and manipulation of quantum states that are used in various quantum technologies. This special issue will focus on new development in relevant topics of estimation and control methods in quantum systems, and provide a forum for idea exchange in this dynamic research area. Particularly, Ian R. Petersen, a key figure in the development of robust and quantum control theory, just turned 60 in the past year. We propose to celebrate this occasion with this special issue on quantum control, one of his main research focuses in the last fifteen years....     

上海世博会突发事件应急预案系统研究

针对中国2010年上海世博会可能发生的各类突发事件,提出应集成运用数据库、GIS、数学模型、专家系统等多种技术手段,特别是提出采用CBR技术,开发世博会突发事件应急预案系统,以提高世博会运行管理时期对各类突发事件的预防和处理处置能力;指出应急预案的主要研究工作应包括应急预案的种类、内容、支撑技术体系,以及应急预案系统的规划、建设与运行管理等;给出了需要解决的关键技术问题和系统开发方案。     

Rethinking technology on the boundaries of life and work

Technology is often seen as seamless, or making (life/work) boundaries go away. Ubicomp designs for that and for seamlessness in general. However, there may be better ways of understanding boundaries, as to design technologies in the space of changing work/life boundaries, which is the topic of this special issue. This paper makes a theoretical argument to insist that boundaries are not fixed, neither can or should they be made away with technologically, through seamless technologies. Based on this argument, it discusses various presumed technology-mediated boundaries of work and home, life, etc., as they can be found in the Ubicomp, CSCW and HCI literature: The ways in which work and work technologies are stereotypically connected to effectiveness and hard labor, and non-work technologies to fun and enjoyment; the ways in which technologies move back and forth between mediating work activity and non-work; the role of place and time boundaries in relation to the ability to work any time, anywhere and the metaphors used to address these boundaries; and the perceived boundaries of private versus public, and the new boundaries created by technologies in and across our lives and work. Using an empirical case, the paper offers an alternative use of boundaries as resources to be activated and used in design. It suggests that we need to more carefully design technologies that provide seamfulness on these specific and dynamic boundaries.     

Pervasive location acquisition technologies: Opportunities and challenges for geospatial studies

The rapid development and increasing availability of various location acquisition technologies provide geospatial studies with both opportunities and challenges. These opportunities and challenges are discussed in this paper focusing on the following three aspects: the massive acquisition of location data and data quality, the analysis of massive location data and pattern discovery, and privacy protection for massive location data. This paper examines the current status of and the potential opportunities for geospatial research in these three areas and notes the major challenges. Finally, the development of this special issue is described, and the four articles included in this special issue are presented.