3,675 research outputs found
Delivery lead time compression an integral part of a time based strategy
The objective of this study is to examine factors influencing delivery lead time in a manufacturing environment. It presents the results of a survey of the electronic and other electrical equipment and components industry\u27 in California to illustrate the relative importance of these factors in delivery time reduction. The degree of importance of each factor is then compared with the extent of emphasis the survey participants actually placed on the factor in attempting to reduce delivery lead time
An innovative framework for real-time monitoring of pollutant point sources in river networks
Simultaneous identification of the location and release history of pollutant sources in river networks is an ill-posed and complicated problem, particularly in the case of multiple sources with time-varying release patterns. This study presents an innovative method for solving this problem using minimum observational data. To do so, a procedure is proposed in which, the number and the suspected reaches to the existence of pollutant sources are determined. This is done by defining two different types of monitoring stations with an adaptive arrangement in addition to real-time data collection and reliable flow and transport mathematical models. In the next step, the sources’ location and their release history are identified by solving the inverse source problem employing a geostatistical approach. Different scenarios are discussed for different conditions of number, release history and location of pollutant sources in the river network. Results indicated the capability of the proposed method in identifying the characteristics of the sources in complicated cases. Hence, it can be effectively used for the comprehensive monitoring of river networks for different purposes
An interface to retrieve personal memories using an iconic visual language
Relevant past events can be remembered when visualizing related pictures. The main difficulty is how to find these photos in a large personal collection. Query definition and image annotation are key issues to overcome this problem. The former is relevant due to the diversity of the clues provided by our memory when recovering a past moment and the later because images need to be annotated with information regarding those clues to be retrieved. Consequently, tools to recover past memories should deal carefully with these two tasks. This paper describes a user interface designed to explore pictures from personal memories. Users can query the media collection in several ways and for this reason an iconic visual language to define queries is proposed. Automatic and semi-automatic annotation is also performed using the image content and the audio information obtained when users show their images to others. The paper also presents the user interface evaluation based on tests with 58 participants
Estimation of biodiesel properties from chemical composition – an artificial neural network (ANN) approach
Biodiesel, produced from renewable feedstock represents a more sustainable source of energy and will therefore play a significant role in providing the energy requirements for transportation in the near future. Chemically, all biodiesels are fatty acid methyl esters (FAME), produced from raw vegetable oil and animal fat. However, clear differences in chemical structure are apparent from one feedstock to the next in terms of chain length, degree of unsaturation, number of double bonds and double bond configuration-which all determine the fuel properties of biodiesel. In this study, prediction models were developed to estimate kinematic viscosity of biodiesel using an Artificial Neural Network (ANN) modelling technique. While developing the model, 27 parameters based on chemical composition commonly found in biodiesel were used as the input variables and kinematic viscosity of biodiesel was used as output variable. Necessary data to develop and simulate the network were collected from more than 120 published peer reviewed papers. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture and learning algorithm were optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the coefficient of determination (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found high predictive accuracy of the ANN in predicting fuel properties of biodiesel and has demonstrated the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties. Therefore the model developed in this study can be a useful tool to accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests
Inferring Networks of Substitutable and Complementary Products
In a modern recommender system, it is important to understand how products
relate to each other. For example, while a user is looking for mobile phones,
it might make sense to recommend other phones, but once they buy a phone, we
might instead want to recommend batteries, cases, or chargers. These two types
of recommendations are referred to as substitutes and complements: substitutes
are products that can be purchased instead of each other, while complements are
products that can be purchased in addition to each other.
Here we develop a method to infer networks of substitutable and complementary
products. We formulate this as a supervised link prediction task, where we
learn the semantics of substitutes and complements from data associated with
products. The primary source of data we use is the text of product reviews,
though our method also makes use of features such as ratings, specifications,
prices, and brands. Methodologically, we build topic models that are trained to
automatically discover topics from text that are successful at predicting and
explaining such relationships. Experimentally, we evaluate our system on the
Amazon product catalog, a large dataset consisting of 9 million products, 237
million links, and 144 million reviews.Comment: 12 pages, 6 figure
Laboratory Evaluation of Five Chitin Synthesis Inhibitors Against the Colorado Potato Beetle, Leptinotarsa decemlineata
Results of laboratory experiments are reported that tested the effects of five chitin synthesis inhibitors, diflubenzuron, cyromazine, lufenuron, hexaflumuron and triflumuron. on second instars of the Colorado potato beetle, Leptinotarsa decemlineata (Say) (Coleoptera: Crysomelidae), originally collected from potato fields of Bostanabaad, a town 66 km southeast of Tabriz, Iran. In bioassays, the larvae were fed potato leaves dipped in aqueous solutions containing chitin synthesis inhibitors. The mortalities and abnormalities of the treated larvae were recorded 72 hours after treatments. LC50 values were 58.6, 69.6, 27.3, 0.79 and 81.4 mg ai/ L for diflubenzuron, cyromazine, lufenuron, hexaflumuron and triflumuron, respectively. Compared with phosalone, which is one of the common insecticides used for controlling this pest in Iran, lufenuron and hexaflumuron seem to be much more potent, and if they perform equally well in the field, they would be suitable candidates to be considered as reduced risk insecticides in management programs for L. decemlineata due to much wider margin of safety for mammals and considerably fewer undesirable environmental side effects
Towards real-time classification of astronomical transients
Exploration of time domain is now a vibrant area of research in astronomy, driven by the advent of digital synoptic sky surveys. While panoramic surveys can detect variable or transient events, typically some follow-up observations are needed; for short-lived phenomena, a rapid response is essential. Ability to automatically classify and prioritize transient events for follow-up studies becomes critical as the data rates increase. We have been developing such methods using the data streams from the Palomar-Quest survey, the Catalina Sky Survey and others, using the VOEventNet framework. The goal is to automatically classify transient events, using the new measurements, combined with archival data (previous and multi-wavelength measurements), and contextual information (e.g., Galactic or ecliptic latitude, presence of a possible host galaxy nearby, etc.); and to iterate them dynamically as the follow-up data come in (e.g., light curves or colors). We have been investigating Bayesian methodologies for classification, as well as discriminated follow-up to optimize the use of available resources, including Naive Bayesian approach, and the non-parametric Gaussian process regression. We will also be deploying variants of the traditional machine learning techniques such as Neural Nets and Support Vector Machines on datasets of reliably classified transients as they build up
Posterior sub-tenon's bevacizumab injection in diabetic macular edema; a pilot study
Purpose: To evaluate the short-term results of sub-tenon's injection of bevacizumab in patients with clinically significant macular edema (CSME). Methods: In this prospective non-comparative interventional case series, sub-tenon's injection of 2.5. mg/0.1. ml bevacizumab was performed for eyes with CSME. Macular thickness and best corrected visual acuity measurements were performed before and one month after injections. Results: Nineteen eyes of twelve patients with a mean age of 59.8. ±. 5.7. years were evaluated. Thirteen eyes (68.4) had center-involving macular edema. No significant difference was observed between pre- and post-injection central subfield retinal thickness measurements (P= 0.3). Central subfield thickness measurements improved or remained unchanged in 13 eyes (68.4). Baseline BCVA of 0.48. ±. 0.35 LogMAR improved to 0.36. ±. 0.26 LogMAR after injection (P= 0.01). Improvement of. > 2 lines in BCVA was found in 5 eyes (26.3), and no eye lost. > 2 lines of BCVA. No complication associated with sub-tenon's injection was observed. Conclusion: Sub-tenon's injection of bevacizumab resulted in significant short-term visual improvement in eyes with CSME. Retinal thickness changes were not significant. © 2015 The Authors
Parasitic infection among larvae and fingerlings of the Persian sturgeon (Acipenser persicus) in Vniro tanks and earthen ponds
This study was conducted in two phases on sturgeon larvae and fingerlings produced from artificial breeding of five pairs of the Persian sturgeon (Acipenser persicus) broodstocks in Shahid Beheshti Hatchery in spring and summer 2006. Initially, 600 larvae were collected on 3 post days hatching (pdh) and 5 days after the onset of exogenous feeding. The second phase was conducted with 450 specimens collected from five earthen ponds, which included 150 larvae collected one week after stocking, 150 fingerlings collected 20 days after stocking and 150 fingerlings collected at the time of their release into rivers. No parasite was observed in the sturgeon larvae on day 3 pdh and 5 days after the onset of exogenous feeding. However Trichodina reticulata were observed in the larvae in the first week (prevalence = 10 - 20%) and also in the fingerlings (prevalence = 10 - 46.67%) 20 days after they were transferred to the earthen ponds. At the time of their release into the river, in addition to T. reticulata (prevalence = 13.33 – 100%) a digenean trematode, Diplostomum spathaceum, (prevalence = 6.67 - 30%) was also observed in the sturgeon fingerlings. It is evident from the present study that Trichodina and Diplostomum infection occurs after fingerlings are released into the earthen ponds and gradually increases with the progress in the rearing period. Increase in prevalence of Trichodina infection through the rearing period can be explained by the increase in water temperature and increase in dissolved organic matter in the ponds which provide the desirable conditions for the propagation of this unicellular ciliate. Significant differences were observed in the mean intensity of T. reticulata infection in sturgeon fingerlings during different stages of rearing into earthen ponds (P<0.05)
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