to study the effects of two irrigation regimes and application of barley residue, zeolite and superabsorbent polymer on forage yield and some physiological traits of maize and sorghum, an experiment was conducted over two years in kerman, iran. a randomized complete block design arranged in a factorial split was used with three replications. two irrigation regimes of normal irrigation and water...

Zero-shot Recognition (ZSR) is to learn recognition models for novel classes without labeled data. It is a challenging task and has drawn considerable attention in recent years. The basic idea is to transfer knowledge from seen classes via the shared attributes. This paper focus on the transductive ZSR, i.e., we have unlabeled data for novel classes. Instead of learning models for seen and nove...

Zeta sedimentation ratio (ZSR) is a simple, rapid and reproducible test which is not influenced by variables like sex and anemia. There is good correlation with Westergren erythrocyte sedimentation ratio (ESR) in normal and hospital population. Limitation of packing force affects the use of the procedure in polycythemia and in patients with ZSR greater than 80%.

As an interesting and emerging topic, zero-shot recognition (ZSR) makes it possible to train a recognition model by specifying the category’s attributes when there are no labeled exemplars available. The fundamental idea for ZSR is to transfer knowledge from the abundant labeled data in different but related source classes via the class attributes. Conventional ZSR approaches adopt a two-step s...

Zero-shot recognition (ZSR) deals with the problem of predicting class labels for target domain instances based on source domain side information (e.g. attributes) of unseen classes. We formulate ZSR as a binary prediction problem. Our resulting classifier is class-independent. It takes an arbitrary pair of source and target domain instances as input and predicts whether or not they come from t...

Zero-shot recognition (ZSR) aims to recognize targetdomain data instances of unseen classes based on the models learned from associated pairs of seen-class source and target domain data. One of the key challenges in ZSR is the relative scarcity of source-domain features (e.g. one feature vector per class), which do not fully account for wide variability in target-domain instances. In this paper...

1 Institute of Particle Physics, ETH Hönggerberg, CH-8093 Zürich, Switzerland 2 Dept. für Chemie und Biochemie, Universität Bern, CH-3012 Bern, Switzerland 3 Dpto. Fisica Atomica, Universidad de Sevilla, E-41012 Sevilla, Spain 4 ZSR, Universität Hannover, D-30167 Hannover, Germany 5 Institute for Atmospheric and Climate Science, ETH Hönggerberg, CH-8093 Zürich, Switzerland 6 EAWAG, Ueberlandstr...

The organic fraction of atmospheric aerosols contains a multitude of compounds and usually only a small fraction can be identified and quantified. However, a limited number of representative organic compounds can be used to describe the water-soluble organic fraction. In this work, initiated within the EU 5FP project SMOCC, four mixtures containing various amounts of inorganic salts (ammonium s...

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