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Geometric generalization is a fundamental concept in the digital mapping process. An increasing amount of spatial data is provided on the web as well as a range of tools to process it. This jABC workflow is used for the automatic testing of web-based generalization services like mapshaper.org by executing its functionality, overlaying both datasets before and after the transformation and displaying them visually in a .tif file. Mostly Web Services and command line tools are used to build an environment where ESRI shapefiles can be uploaded, processed through a chosen generalization service and finally visualized in Irfanview.
Where girls the role of boys in CS - attitudes of CS students in a female-dominated environment
(2013)
With the success of wireless technologies in consumer electronics, standard wireless technologies are envisioned for the deployment in industrial environments as well. Industrial applications involving mobile subsystems or just the desire to save cabling make wireless technologies attractive. Nevertheless, these applications often have stringent requirements on reliability and timing. In wired environments, timing and reliability are well catered for by fieldbus systems (which are a mature technology designed to enable communication between digital controllers and the sensors and actuators interfacing to a physical process). When wireless links are included, reliability and timing requirements are significantly more difficult to meet, due to the adverse properties of the radio channels. In this paper we thus discuss some key issues coming up in wireless fieldbus and wireless industrial communication systems:1)fundamental problems like achieving timely and reliable transmission despite channel errors; 2) the usage of existing wireless technologies for this specific field of applications; and 3) the creation of hybrid systems in which wireless stations are included into existing wired systems
Analyses of metagenomes in life sciences present new opportunities as well as challenges to the scientific community and call for advanced computational methods and workflows. The large amount of data collected from samples via next-generation sequencing (NGS) technologies render manual approaches to sequence comparison and annotation unsuitable. Rather, fast and efficient computational pipelines are needed to provide comprehensive statistics and summaries and enable the researcher to choose appropriate tools for more specific analyses. The workflow presented here builds upon previous pipelines designed for automated clustering and annotation of raw sequence reads obtained from next-generation sequencing technologies such as 454 and Illumina. Employing specialized algorithms, the sequence reads are processed at three different levels. First, raw reads are clustered at high similarity cutoff to yield clusters which can be exported as multifasta files for further analyses. Independently, open reading frames (ORFs) are predicted from raw reads and clustered at two strictness levels to yield sets of non-redundant sequences and ORF families. Furthermore, single ORFs are annotated by performing searches against the Pfam database
Workshop on Implementing Automata : WIA99 - pre-proceedings ; Potsdam, Germany, 17 - 19. July 1999
(1999)
Using the timing flexibility of modern automatic test equipment (ATE) test response data can be compacted without the need for additional X-masking logic. In this article the test response is compacted by several multiple input shift registers without feedback (NF-MISR). The shift registers are running on a k-times higher clock frequency than the test clock. For each test clock cycle only one out of the k outputs of each shift register is evaluated by the ATE. The impact of consecutive X values within the scan chains is reduced by a periodic permutation of the NF-MISR inputs. As a result, no additional external control signals or test set dependent control logic is required. The benefits of the proposed method are shown by the example of an implementation on a Verigy ATE. Experiments on three industrial circuits demonstrate the effectiveness of the proposed approach in comparison to a commercial DFT solution.
The exponential expanding of the numbers of web sites and Internet users makes WWW the most important global information resource. From information publishing and electronic commerce to entertainment and social networking, the Web allows an inexpensive and efficient access to the services provided by individuals and institutions. The basic units for distributing these services are the web sites scattered throughout the world. However, the extreme fragility of web services and content, the high competence between similar services supplied by different sites, and the wide geographic distributions of the web users drive the urgent requirement from the web managers to track and understand the usage interest of their web customers. This thesis, "X-tracking the Usage Interest on Web Sites", aims to fulfill this requirement. "X" stands two meanings: one is that the usage interest differs from various web sites, and the other is that usage interest is depicted from multi aspects: internal and external, structural and conceptual, objective and subjective. "Tracking" shows that our concentration is on locating and measuring the differences and changes among usage patterns. This thesis presents the methodologies on discovering usage interest on three kinds of web sites: the public information portal site, e-learning site that provides kinds of streaming lectures and social site that supplies the public discussions on IT issues. On different sites, we concentrate on different issues related with mining usage interest. The educational information portal sites were the first implementation scenarios on discovering usage patterns and optimizing the organization of web services. In such cases, the usage patterns are modeled as frequent page sets, navigation paths, navigation structures or graphs. However, a necessary requirement is to rebuild the individual behaviors from usage history. We give a systematic study on how to rebuild individual behaviors. Besides, this thesis shows a new strategy on building content clusters based on pair browsing retrieved from usage logs. The difference between such clusters and the original web structure displays the distance between the destinations from usage side and the expectations from design side. Moreover, we study the problem on tracking the changes of usage patterns in their life cycles. The changes are described from internal side integrating conceptual and structure features, and from external side for the physical features; and described from local side measuring the difference between two time spans, and global side showing the change tendency along the life cycle. A platform, Web-Cares, is developed to discover the usage interest, to measure the difference between usage interest and site expectation and to track the changes of usage patterns. E-learning site provides the teaching materials such as slides, recorded lecture videos and exercise sheets. We focus on discovering the learning interest on streaming lectures, such as real medias, mp4 and flash clips. Compared to the information portal site, the usage on streaming lectures encapsulates the variables such as viewing time and actions during learning processes. The learning interest is discovered in the form of answering 6 questions, which covers finding the relations between pieces of lectures and the preference among different forms of lectures. We prefer on detecting the changes of learning interest on the same course from different semesters. The differences on the content and structure between two courses leverage the changes on the learning interest. We give an algorithm on measuring the difference on learning interest integrated with similarity comparison between courses. A search engine, TASK-Moniminer, is created to help the teacher query the learning interest on their streaming lectures on tele-TASK site. Social site acts as an online community attracting web users to discuss the common topics and share their interesting information. Compared to the public information portal site and e-learning web site, the rich interactions among users and web content bring the wider range of content quality, on the other hand, provide more possibilities to express and model usage interest. We propose a framework on finding and recommending high reputation articles in a social site. We observed that the reputation is classified into global and local categories; the quality of the articles having high reputation is related with the content features. Based on these observations, our framework is implemented firstly by finding the articles having global or local reputation, and secondly clustering articles based on their content relations, and then the articles are selected and recommended from each cluster based on their reputation ranks.