Persistent problems and practices in information systems development: a study of mobile applications development and distribution

The widespread uptake of mobile technologies has witnessed a re‐structuring of the mobile market with major shifts in the predominance of particular firms and the emergence of new business models. These sociotechnical trends are significant in the ways that they are influencing and shaping the working lives of software professionals. Building on prior research investigating the persistent problems and practices of systems development, this paper examines mobile applications development and distribution. A qualitative study of 60 developers based in Sweden, the UK and the USA was analysed around the interrelated problems of diversity, knowledge and structure. The analysis revealed how platform‐based development in an evolving mobile market represents significant changes at the business environment level. These changes ripple through and accentuate ongoing trends and developments, intensifying the persistent problems and challenges facing software developers.     

The (Uncertain) Future of Libraries in a Google World

Abstract

Libraries are in competition with other entities that provide information access to students, scholars and the general public. This constitutes a radical change in the information environment. The library profession's failure to take seriously the change that has taken place in the information environment, and to respond with fundamental changes of its own, may well spell disaster for the library as we know it.     

Google and Privacy

Abstract

Google has emerged as the preeminent Internet search engine, but more important, it has achieved an iconic status. It is solidly entrenched in our language and popular culture. But there is a darker side to Google. Google collects personal information about its users, and it aggregates third party information more effectively than many third world governments. While there has been no abuse (that we know of) by Google of personal information, that potential exists, and there are numerous instances of third parties using Google to aggregate personal information for dubious purposes.     

Google体系结构分析

为了适应大规模广范围高密度的搜索,Google的网络搜索应用允许在不同的处理器上运行不同的查询;同时,通过对全局索引进行分解,Google也允许在多个处理器上运行单一的查询.Google的主旨是,使用市场上流行的具有通用的PC,以达到大型机所具有的高性能.通过对已有资料进行搜集,对Google的体系结构、工作性能等进行分析,目的是通过对Google的调研,给网格建设提供一定的借鉴.     

Google一下邻居中有没色狼

按理说,在全球化的21世纪没有什么比个人隐私更重要的事情了,不要说女性的芳龄是绝密数据,这年头连大男人的工资也是问不得的。但在美国,有一家名叫“mapsexoffenders”的网站,打开一看淮保吓你一跳一一“保护你的家庭免受色狼侵害,全国有超过30万性侵害者,点击此处查一查你住的小区有多少流氓”……     

A scalable approach to mapping annual land cover at 250 m using MODIS time series data: A case study in the Dry Chaco ecoregion of South America

Land use and land cover (LULC) maps from remote sensing are vital for monitoring, understanding and predicting the effects of complex human-nature interactions that span local, regional and global scales. We present a method to map annual LULC at a regional spatial scale with source data and processing techniques that permit scaling to broader spatial and temporal scales, while maintaining a consistent classification scheme and accuracy. Using the Dry Chaco ecoregion in Argentina, Bolivia and Paraguay as a test site, we derived a suite of predictor variables from 2001 to 2007 from the MODIS 250 m vegetation index product (MOD13Q1). These variables included: annual statistics of red, near infrared, and enhanced vegetation index (EVI), phenological metrics derived from EVI time series data, and slope and elevation. For reference data, we visually interpreted percent cover of eight classes at locations with high-resolution QuickBird imagery in Google Earth. An adjustable majority cover threshold was used to assign samples to a dominant class. When compared to field data, we found this imagery to have georeferencing error < 5% the length of a MODIS pixel, while most class interpretation error was related to confusion between agriculture and herbaceous vegetation. We used the Random Forests classifier to identify the best sets of predictor variables and percent cover thresholds for discriminating our LULC classes. The best variable set included all predictor variables and a cover threshold of 80%. This optimal Random Forests was used to map LULC for each year between 2001 and 2007, followed by a per-pixel, 3-year temporal filter to remove disallowed LULC transitions. Our sequence of maps had an overall accuracy of 79.3%, producer accuracy from 51.4% (plantation) to 95.8% (woody vegetation), and user accuracy from 58.9% (herbaceous vegetation) to 100.0% (water). We attributed map class confusion to limited spectral information, sub-pixel spectral mixing, georeferencing error and human error in interpreting reference samples. We used our maps to assess woody vegetation change in the Dry Chaco from 2002 to 2006, which was characterized by rapid deforestation related to soybean and planted pasture expansion. This method can be easily applied to other regions or continents to produce spatially and temporally consistent information on annual LULC.     

一种面向维文网站的动态天气图文信息服务支持系统

维吾尔文地理信息服务的研究与应用的匮乏,使维吾尔用户很难享受基于本民族语言的地理信息服务。该文以新疆动态天气图文信息服务为例,提出了一种面向维文网站的WebGIS服务解决方案。方案首先通过集成免费Google Maps API地图服务和实时免费Yahoo Weather RSS天气信息,制作新疆县域维吾尔文天气信息服务模块;其次,将该模块作为引用对象,根据用户对动态天气图文信息服务框架大小和位置的设定,个性化地嵌入到任意维吾尔文大众网站中,使更广大的维吾尔用户享受WebGIS带来的信息服务。该研究推动了WebGIS在维吾尔语语境的新应用,为新疆各族群众提供了便捷动态天气图文信息服务。     

Google Maps API在林业局级林下作物栽培中的应用

林下经济以其能够充分利用林下土地资源及大面积林荫的优势而得到众多农林专家和林农的青睐,其在实现农林资源共享、优势互补和循环生态方面发挥着很大的作用。结合林下经济发展现状及广大林农的需求特点,综合运用当前先进的Google Maps API技术和A-JAX技术,以JSON作为客户端与服务器的数据传送格式,构建基于B/S的林业局级林下作物栽培咨询平台。该平台提供给用户直观化的信息查询与呈现效果,不仅有效提高农户种植的科学性,也可在一定程度上帮助管理层制定决策。     

在移动环境下基于Android的车辆位置信息监控应用研究

提出基于Android的车辆位置信息监控,通过建立Web服务发布车辆的GPS信息,利用Android平台的强大的网络功能及Google Maps位置感知,解决了在移动环境下车辆GPS监控系统对车辆位置信息进行监控的问题。     

如何使用Java实现对Google引擎服务接口的调用

对Google搜索引擎的工作原理进行了详细分析，同时介绍了Google公司新近推出的WebServices接口服务，简单地描述了WebServices相关技术，最后举了一个具体的应用实例。