Fast and successful searching for an object in a multimedia database is a highly desirable functionality. Several approaches to content based retrieval for multimedia databases can be found in the literature [9,10,12,14,17]. The approach we consider is feature extraction. A feature can be seen as a way to present simple information like the texture, color and spatial information of an image, or the pitch, frequency of a sound etc. In this paper we present a method for feature extraction on texture and spatial similarity, using fractal coding techniques. Our method is based upon the observation that the coefficients describing the fractal code of an image, contain very useful information about the structural content of the image. We apply simple statistics on information produced by fractal image coding. The statistics reveal features and require a small amount of storage. Several invariances are a consequence of the used methods: size, global contrast, orientation.
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A common strategy to assign keywords to documents is to select the most appropriate words from the document text. One of the most important criteria for a word to be selected as keyword is its relevance for the text. The tf.idf score of a term is a widely used relevance measure. While easy to compute and giving quite satisfactory results, this measure does not take (semantic) relations between words into account. In this paper we study some alternative relevance measures that do use relations between words. They are computed by defining co-occurrence distributions for words and comparing these distributions with the document and the corpus distribution. We then evaluate keyword extraction algorithms defined by selecting different relevance measures. For two corpora of abstracts with manually assigned keywords, we compare manually extracted keywords with different automatically extracted ones. The results show that using word co-occurrence information can improve precision and recall over tf.idf.
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Sensor systems can be deployed in the homes of older adults living alone for functional health assessments. Their information is very useful for health care specialists. The problem lies in developing person independent models while facing a large variability in behavior. We address this problem by, first, proposing a new feature extraction method for data from ambient motion sensors. The method uses functional similarities between houses and daily structure to extract meaningful features. Second, we propose a change-based approach for analyzing data, taking difference scores of both the sensor features and health metrics. To evaluate our approach, experiments on longitudinal data were conducted, where the relationship between sensor data and health measurements was modeled with linear regression and (nonlinear) regression forests. These experiments show that the change-based approach yields better results and that the resulting models can be used as a reliable metric for (functional) health. In addition, feature analysis can help health care specialists understand relevant aspects of behavior. Prediction of health metrics is possible even with simple sensors. With such sensors, it is possible to detect problems and health decline in an early stage. This will have great impact on clinical practice.
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Kumasi and RokitScience contribute to increasing the ownership and income of cocoa farmers, with an emphasis on women. Kumasi has a successful history of developing and marketing cocoa juice, which aims to keep as much income as possible with the farmer. RokitScience has been involved in the creation of the Rokbar: a "bean to bar" empowering chocolate bar that is marketed and made entirely by women. Kumasi and RokitScience started setting up a cocoa-fruit-lab at the cocoa-cooperative COVIMA in early 2021 in Ivory-Coast, in collaboration with Beyond Beans Foundation/ETG and Döhler and financially supported by the Sustainable-Trade-Initiative (IDH). The goal is to support the cooperative, which is led by women, with the establishment of circular cocoa juice and chocolate production and in this way increase the income of the members of the cooperative. The cocoa pod contains cocoa beans embedded in cocoa pulp. This pulp is sweet and juicy and partly needed for cocoa bean fermentation for flavor development. Residual pulp can be used for new products like drinks, marmalades and more. The collaboration in the cocoa fruit lab created momentum to try-out a more circular approach whereby the extraction of juice was linked to a shorter fermentation period of the beans, influencing quality features of both the beans and potentially the chocolate. However, to optimize the production of juicy beans further and find a market for this (and potentially other) products requires further testing and development of a value proposition and marketing strategy. The main question of Kumasi and RokitScience at Hanzehogeschool Groningen and NHLStenden Hogeschool Amsterdam is: What is the effect on the quality of beans and chocolate if fermented after the extraction of juice? How can this be optimized: comparing ‘cocoa of excellence’ fermentation and drying to traditional post-harvest practices and how can we tell the world?
Kumasi and RokitScience contribute to increasing the ownership and income of cocoa farmers, with an emphasis on women. Kumasi has a successful history of developing and marketing cocoa juice, which aims to keep as much income as possible with the farmer. RokitScience has been involved in the creation of the Rokbar: a "bean to bar" empowering chocolate bar that is marketed and made entirely by women. Kumasi and RokitScience started setting up a cocoa-fruit-lab at the cocoa-cooperative COVIMA in early 2021 in Ivory-Coast, in collaboration with Beyond Beans Foundation/ETG and Döhler and financially supported by the Sustainable-Trade-Initiative (IDH). The goal is to support the cooperative, which is led by women, with the establishment of circular cocoa juice and chocolate production and in this way increase the income of the members of the cooperative. The cocoa pod contains cocoa beans embedded in cocoa pulp. This pulp is sweet and juicy and partly needed for cocoa bean fermentation for flavor development. Residual pulp can be used for new products like drinks, marmalades and more. The collaboration in the cocoa fruit lab created momentum to try-out a more circular approach whereby the extraction of juice was linked to a shorter fermentation period of the beans, influencing quality features of both the beans and potentially the chocolate. However, to optimize the production of juicy beans further and find a market for this (and potentially other) products requires further testing and development of a value proposition and marketing strategy.The main question of Kumasi and RokitScience at Hanzeschool Groningen and Hogeschool Amsterdam is: What is the effect on the quality of beans and chocolate if fermented after the extraction of juice? How can this be optimized: comparing ‘cocoa of excellence’ fermentation and drying to traditional post-harvest practices and how can we tell the world?
