1,721,022 research outputs found
Identificator: a web-based tool for visual plant disease identification, a proof of concept with a case study on strawberry
No full textIdentificator is a web-based tool used to help non experts in identifying plant diseases, based on the selection of pictures and/or short text descriptions (when no suitable images exist) representing the
symptoms on a specific sample of plant organs. The system is based on a multi-access key of identification and specifically on the selection of pictures by the user and can be used remotely from a desktop as well as from a smart phone or personal digital assistant. The system was developed following a simple approach: visual identification where images and/or short descriptions are used to uniquely identify diseases when possible and suggest refining the visual identification process in cases of ambiguous identification. It has been designed in a way that allows easy definition of additional diseases by uploading the correct images and defining the identification rules and diseases. In this way the system may aid growers in identifying various diseases when using the system remotely while the system is developed and maintained centrally. This approach may ease the process of manual visual disease identification until
machine vision technology is mature enough to perform this task automatically. We tested the system for visual identification of strawberry diseases using a computer and samples of infected plants. The evaluation
showed that it is effective and accurate in enabling its users to identify strawberry disease
LAKE system at DUC-2006.
No full textThe paper discusses the third participation of the LAKE system in the DUC-2006 competition. LAKE is a keyphrase based summarizer system that makes use of linguistic analysis to extract keyphrases from documents. Since the past competition it has been also equipped with a module able to extract sentences from documents. As in the past campaign the sys- tem showed a very interesting performance, specially with respect the Linguistic Quality of the summaries created
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Optimization of copper treatments in organic viticulture by using a web-based decision support system
No full textComparing the comprehensibility of requirements models expressed in Use Case and Tropos: Results from a family of experiments
No full text[Context] Over the years, several modeling languages for requirements have been proposed. These languages employ different conceptual approaches, including scenario-based and goal-oriented ones. Empirical studies providing evidence about requirements model comprehensibility are rare, especially when addressing languages that belong to different modeling approaches. [Objective] This work aims to compare the comprehensibility of requirements models expressed in different but comparable modeling approaches from a requirements analysts’ perspective. In particular, in this paper we compare the comprehensibility of requirements models expressed in two visual modeling languages: Use Case, which is scenario-based, and Tropos, which exploits goal-oriented modeling. We further compare the effort required for comprehending the different models, and the derived productivity in each case. [Method] Requirements model comprehensibility is measured here in the context of three types of tasks that analysts usually perform, namely mapping between textual description and the model elements, reading and understanding the model irrespectively of the original textual description, and modifying the model. This experimental evaluation has been conducted within a family of controlled experiments aiming at comparing the comprehensibility of Use Case and Tropos requirements models. Three runs of the experiment were performed, including a first experiment and two replications, involving 79 subjects overall (all of which were information systems students). The data for each experiment was separately analyzed, followed by a meta-analysis of the three experiments. [Results] The experimental results show that Tropos models seem to be more comprehensible with respect to the three types of requirements analysis tasks, although more time consuming than Use Case models. Conclusions Measuring model comprehensibility by means of controlled experiments is feasible and provides a basis for comparing Tropos and Use Case models, although these languages belong to different modeling approaches. Specifically, Tropos outperformed Use Case in terms of comprehensibility, but required more effort leading to a similar productivity of the two languages
Gestione del monitoraggio del colpo di fuoco batterico in Trentino mediante un software che integra diversi modelli previsionali della malattia
No full textBar code labelling system for managing and tracking microbial culture collections and experiments in labs
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