Gives readers a detailed understanding of adsorption refrigeration technology, with a focus on practical applications and environmental concerns Systematically covering the technology of adsorption ...refrigeration, this book provides readers with a technical understanding of the topic as well as detailed information on the state-of-the-art from leading researchers in the field. Introducing readers to background on the development of adsorption refrigeration, the authors also cover the development of adsorbents, various thermodynamic theories, the design of adsorption systems and adsorption refrigeration cycles. The book guides readers through the research process, covering key aspects such as: the principle of adsorption refrigeration; choosing adsorbents according to different characteristics; thermodynamic equations; methods for the design of heat exchangers for adsorbers; and the advanced adsorption cycles needed. It is also valuable as a reference for professionals working in these areas. * Covers state-of-the art of adsorption research and technologies for relevant applications, working from adsorption working pairs through to the application of adsorption refrigeration technology for low grade heat recovery * Assesses sustainable alternatives to traditional refrigeration methods, such as the application of adsorption refrigeration systems for solar energy and waste heat * Includes a key chapter on the design of adsorption refrigeration systems as a tutorial for readers new to the topic; the calculation models for different components and working processes are also included * Takes real-world examples giving an insight into existing products and installations and enabling readers to apply the knowledge to their own work Academics researching low grade energy utilization and refrigeration; Graduate students of refrigeration and low grade energy utilization; Experienced engineers wanting to renew knowledge of adsorption technology,Engineers working at companies developing adsorption chillers; Graduate students working on thermally driven systems; Advanced undergraduates for the Refrigeration Principle as a part of thermal driven refrigeration technology.
Image-language matching tasks have recently attracted a lot of attention in the computer vision field. These tasks include image-sentence matching, i.e., given an image query, retrieving relevant ...sentences and vice versa, and region-phrase matching or visual grounding, i.e., matching a phrase to relevant regions. This paper investigates two-branch neural networks for learning the similarity between these two data modalities. We propose two network structures that produce different output representations. The first one, referred to as an embedding network , learns an explicit shared latent embedding space with a maximum-margin ranking loss and novel neighborhood constraints. Compared to standard triplet sampling, we perform improved neighborhood sampling that takes neighborhood information into consideration while constructing mini-batches. The second network structure, referred to as a similarity network , fuses the two branches via element-wise product and is trained with regression loss to directly predict a similarity score. Extensive experiments show that our networks achieve high accuracies for phrase localization on the Flickr30K Entities dataset and for bi-directional image-sentence retrieval on Flickr30K and MSCOCO datasets.
On the Euclidean distance of images Wang, Liwei; Zhang, Yan; Feng, Jufu
IEEE transactions on pattern analysis and machine intelligence,
08/2005, Letnik:
27, Številka:
8
Journal Article
Recenzirano
We present a new Euclidean distance for images, which we call image Euclidean distance (IMED). Unlike the traditional Euclidean distance, IMED takes into account the spatial relationships of pixels. ...Therefore, it is robust to small perturbation of images. We argue that IMED is the only intuitively reasonable Euclidean distance for images. IMED is then applied to image recognition. The key advantage of this distance measure is that it can be embedded in most image classification techniques such as SVM, LDA, and PCA. The embedding is rather efficient by involving a transformation referred to as standardizing transform (ST). We show that ST is a transform domain smoothing. Using the face recognition technology (FERET) database and two state-of-the-art face identification algorithms, we demonstrate a consistent performance improvement of the algorithms embedded with the new metric over their original versions.
We show that the maximal operator associated with multilinear Calderón-Zygmund singular integrals and its commutators are bounded on products of central Morrey spaces with variable exponent. ...Moreover, some bounded properties are obtained for the commutators of multilinear Calderón-Zygmund operators as well as for the corresponding fractional integrals.
In this review paper, the recent development on the adsorption of organic dyes by metal-doped porous carbon materials were reviewed. The primary objective of this paper is to sort out the dispersion ...information of metal-doped porous carbon materials widely used in organic dye adsorption. Various metal-doped porous carbon materials adsorbing organic dyes are summarized and discussed here for the first time. Key factors affecting the adsorption process such as the amount of doped metal, solution pH, and temperature are also reported and discussed. The adsorption mechanisms such as electrostatic interaction, π-π interaction, hydrogen bonding and synergistic interaction between metal particles and carbon materials are proposed for organic dyes adsorption on metal-doped porous carbon with the help of related works from the literature. Finally, few suggestions for future studies on metal-doped porous carbon materials are proposed.
•The adsorption of organic dyes in wastewater by metal doped porous carbon materials was reviewed for the first time.•Different types of metal doped porous carbon were summarized and their development trends for dye adsorption were analyzed.•The influence factors and mechanism of adsorption were discussed.•Few suggestions for future studying on metal doped porous carbon materials are proposed.
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•Word embeddings trained from clinical notes, literature, Wikipedia, and news are compared.•Word embeddings trained from clinical notes and literature capture word semantics ...better.•There isn’t a consistent global ranking of word embeddings for biomedical NLP applications.•Word embeddings trained from biomedical domain corpora do not necessarily perform better.
Word embeddings have been prevalently used in biomedical Natural Language Processing (NLP) applications due to the ability of the vector representations being able to capture useful semantic properties and linguistic relationships between words. Different textual resources (e.g., Wikipedia and biomedical literature corpus) have been utilized in biomedical NLP to train word embeddings and these word embeddings have been commonly leveraged as feature input to downstream machine learning models. However, there has been little work on evaluating the word embeddings trained from different textual resources.
In this study, we empirically evaluated word embeddings trained from four different corpora, namely clinical notes, biomedical publications, Wikipedia, and news. For the former two resources, we trained word embeddings using unstructured electronic health record (EHR) data available at Mayo Clinic and articles (MedLit) from PubMed Central, respectively. For the latter two resources, we used publicly available pre-trained word embeddings, GloVe and Google News. The evaluation was done qualitatively and quantitatively. For the qualitative evaluation, we randomly selected medical terms from three categories (i.e., disorder, symptom, and drug), and manually inspected the five most similar words computed by embeddings for each term. We also analyzed the word embeddings through a 2-dimensional visualization plot of 377 medical terms. For the quantitative evaluation, we conducted both intrinsic and extrinsic evaluation. For the intrinsic evaluation, we evaluated the word embeddings’ ability to capture medical semantics by measruing the semantic similarity between medical terms using four published datasets: Pedersen’s dataset, Hliaoutakis’s dataset, MayoSRS, and UMNSRS. For the extrinsic evaluation, we applied word embeddings to multiple downstream biomedical NLP applications, including clinical information extraction (IE), biomedical information retrieval (IR), and relation extraction (RE), with data from shared tasks.
The qualitative evaluation shows that the word embeddings trained from EHR and MedLit can find more similar medical terms than those trained from GloVe and Google News. The intrinsic quantitative evaluation verifies that the semantic similarity captured by the word embeddings trained from EHR is closer to human experts’ judgments on all four tested datasets. The extrinsic quantitative evaluation shows that the word embeddings trained on EHR achieved the best F1 score of 0.900 for the clinical IE task; no word embeddings improved the performance for the biomedical IR task; and the word embeddings trained on Google News had the best overall F1 score of 0.790 for the RE task.
Based on the evaluation results, we can draw the following conclusions. First, the word embeddings trained from EHR and MedLit can capture the semantics of medical terms better, and find semantically relevant medical terms closer to human experts’ judgments than those trained from GloVe and Google News. Second, there does not exist a consistent global ranking of word embeddings for all downstream biomedical NLP applications. However, adding word embeddings as extra features will improve results on most downstream tasks. Finally, the word embeddings trained from the biomedical domain corpora do not necessarily have better performance than those trained from the general domain corpora for any downstream biomedical NLP task.
•Intrinsic kinetics of pit/crack initiation induced by inclusions is provided.•Chemical dissolution of complex oxide inclusions induces pits.•Dissolution of CaS generates circular protected region ...around Ds type inclusions.•Si-enriched inclusions remain intact but can induce micro-cracks.
In-situ 2D and 3D microscopic technologies are used to analyze the influence of inclusions on pitting and stress corrosion cracking initiation of X70 steel in near-neutral pH solution. The chemical dissolution of complex oxide inclusions or part of them induces corrosion pits. Circular protected region forms around Ds inclusions due to dissolution of CaS. The Si-enriched inclusions remain intact, but interstice forms at the inclusion/matrix interface due to the dissolution of the matrix. Both complex oxide inclusions and Si-enriched inclusions can induce initiation of SCC micro-cracks, but most of the micro-cracks are generated inside the ferrite grains.
The Flickr30k dataset has become a standard benchmark for sentence-based image description. This paper presents Flickr30k Entities, which augments the 158k captions from Flickr30k with 244k ...coreference chains, linking mentions of the same entities across different captions for the same image, and associating them with 276k manually annotated bounding boxes. Such annotations are essential for continued progress in automatic image description and grounded language understanding. They enable us to define a new benchmark for localization of textual entity mentions in an image. We present a strong baseline for this task that combines an image-text embedding, detectors for common objects, a color classifier, and a bias towards selecting larger objects. While our baseline rivals in accuracy more complex state-of-the-art models, we show that its gains cannot be easily parlayed into improvements on such tasks as image-sentence retrieval, thus underlining the limitations of current methods and the need for further research.
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•A new corrosion form around sulfide-oxide complex inclusion is reported.•Chemical dissolution of CaS generates H2S and deposits, providing the condition for the formation of galvanic ...couple.•CaS and appropriate electrolyte chemistry are prerequisites for the formation of galvanic couples.•Cathode/anode area ratio is calculated to be around 50 based on the statistic data.•Galvanic corrosion disappears as CaS is completely dissolved.
Dissolution kinetics of the sulfide-oxide complex inclusion and its surrounding matrix of X70 steel in deaerated acidic environment was investigated. The dissolution process can be divided into three stages including the initiation stage, galvanic corrosion stage, and the corrosion propagation stage. Chemical dissolution of CaS generates H2S and deposits, providing the condition for the formation of the galvanic couple in which the occluded micro-pits serve as anode and the surrounding matrix serves as cathode. The presence of CaS and appropriate electrolyte chemistry are indispensable for the formation of galvanic couple, of which the cathode/anode area ratio is about 50.
Schematic diagram of controlling factor the SCC process for E690 steel in different solution. (The HE and AD/pitting effect lines represent the relative contribution of these two factor, rather than ...the real values.)
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•Corrosion of E690 steel in the local confined environment in seawater is studied.•Acidification of seawater and addition of thiosulfate increase the cathodic current.•Pitting corrosion occurs in the thiosulfate-containing, acidified seawater.•Hydrogen embrittlement dominates the cracking at low content of thiosulfate.•Occurrence of corrosion pits dominates the cracking at high content of thiosulfate.
Electrochemical corrosion and stress corrosion cracking (SCC) behavior of E690 steel in the aerated, deaerated, acidified and thiosulfate-containing artificial seawater are investigated. Corrosion product is transformed from a single iron oxyhydroxide layer to a stratified structure with an additional outer mackinawite layer after long-time immersion with addition of thiosulfate. The SCC process at low thiosulfate concentration (10−4 M) is mainly dominated by hydrogen embrittlement because of the thiosulfate-induced promotion of hydrogen permeation. At high thiosulfate concentration (10−2 M), occurrence of severe pitting corrosion leads to the highest SCC susceptibility despite that the formation of continuous mackinawite inhibits hydrogen permeation.
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