Modelling dosator filling and discharge of powder

Dosators and other dosing mechanisms operating on generally similar principles are very widely used in the pharmaceutical industry for capsule filling, and for dosing products that are delivered to the customer in powder form such as inhalers. This is a trend that is set to increase. However a significant problem for this technology is being able to predict how accurately and reliably, new drug formulations will be dosed from these machines prior to manufacture. This paper presents a review of the literature relating to powder dosators which considers mathematical models for predicting dosator performance, the effects of the dosator geometry and machine settings on the accuracy of the dose weight. An overview of a model based on classical powder mechanics theory that has been developed at The University of Greenwich is presented. The model uses inputs from a range of powder characterisation tests including, wall friction, bulk density, stress ratio and permeability. To validate the model it is anticipated that it will be trialled for a range of powders alongside a single shot dosator test rig.

Towards Cloud-Based Knowledge Capturing Based on Natural Language Processing

Paper presented at the Cloud Forward Conference 2015, October 6th-8th, Pisa

English Channel towed sledge seabed images. Phase 1: scoping study and example analysis

During the 1970’s and 1980’s, the late Dr Norman Holme undertook extensive towed sledge surveys in the English Channel and some in the Irish Sea. Only a minority of the resulting images were analysed and reported before his death in 1989 but logbooks, video and film material has been archived in the National Marine Biological Library (NMBL) in Plymouth. A scoping study was therefore commissioned by the Joint Nature Conservation Committee and as a part of the Mapping European Seabed Habitats (MESH) project to identify the value of the material archived and the procedure and cost to undertake further work. The results of the scoping study are: 1. NMBL archives hold 106 videotapes (reel-to-reel Sony HD format) and 59 video cassettes (including 15 from the Irish Sea) in VHS format together with 90 rolls of 35 mm colour transparency film (various lengths up to about 240 frames per film). These are stored in the Archive Room, either in a storage cabinet or in original film canisters. 2. Reel-to-reel material is extensive and had already been selectively copied to VHS cassettes. The cost of transferring it to an accepted ‘long-life’ medium (Betamax) would be approximately £15,000. It was not possible to view the tapes as a suitable machine was not located. The value of the tapes is uncertain but they are likely to become beyond salvation within one to two years. 3. Video cassette material is in good condition and is expected to remain so for several more years at least. Images viewed were generally of poor quality and the speed of tow often makes pictures blurred. No immediate action is required. 4. Colour transparency films are in good condition and the images are very clear. They provide the best source of information for mapping seabed biotopes. They should be scanned to digital format but inexpensive fast copying is problematic as there are no between-frame breaks between images and machines need to centre the image based on between-frame breaks. The minimum cost to scan all of the images commercially is approximately £6,000 and could be as much as £40,000 on some quotations. There is a further cost in coding and databasing each image and, all-in-all it would seem most economic to purchase a ‘continuous film’ scanner and undertake the work in-house. 5. Positional information in ships logs has been matched to films and to video tapes. Decca Chain co-ordinates recorded in the logbooks have been converted to latitude and longitude (degrees, minutes and seconds) and a further routine developed to convert to degrees and decimal degrees required for GIS mapping. However, it is unclear whether corrections to Decca positions were applied at the time the position was noted. Tow tracks have been mapped onto an electronic copy of a Hydrographic Office chart. 6. The positions of start and end of each tow were entered to a spread sheet so that they can be displayed on GIS or on a Hydrographic Office Chart backdrop. The cost of the Hydrographic Office chart backdrop at a scale of 1:75,000 for the whole area was £458 incl. VAT. 7. Viewing all of the video cassettes to note habitats and biological communities, even by an experienced marine biologist, would take at least in the order of 200 hours and is not recommended. English Channel towed sledge seabed images. Phase 1: scoping study and example analysis. 6 8. Once colour transparencies are scanned and indexed, viewing to identify seabed habitats and biological communities would probably take about 100 hours for an experienced marine biologist and is recommended. 9. It is expected that identifying biotopes along approximately 1 km lengths of each tow would be feasible although uncertainties about Decca co-ordinate corrections and exact positions of images most likely gives a ±250 m position error. More work to locate each image accurately and solve the Decca correction question would improve accuracy of image location. 10. Using codings (produced by Holme to identify different seabed types), and some viewing of video and transparency material, 10 biotopes have been identified, although more would be added as a result of full analysis. 11. Using the data available from the Holme archive, it is possible to populate various fields within the Marine Recorder database. The overall ‘survey’ will be ‘English Channel towed video sled survey’. The ‘events’ become the 104 tows. Each tow could be described as four samples, i.e. the start and end of the tow and two areas in the middle to give examples along the length of the tow. These samples would have their own latitude/longitude co-ordinates. The four samples would link to a GIS map. 12. Stills and video clips together with text information could be incorporated into a multimedia presentation, to demonstrate the range of level seabed types found along a part of the northern English Channel. More recent images taken during SCUBA diving of reef habitats in the same area as the towed sledge surveys could be added to the Holme images.

Analysis of classification accuracy for pre-filtered multichannel remote sensing data

Noise is one of the main factors degrading the quality of original multichannel remote sensing data and its presence influences classification efficiency, object detection, etc. Thus, pre-filtering is often used to remove noise and improve the solving of final tasks of multichannel remote sensing. Recent studies indicate that a classical model of additive noise is not adequate enough for images formed by modern multichannel sensors operating in visible and infrared bands. However, this fact is often ignored by researchers designing noise removal methods and algorithms. Because of this, we focus on the classification of multichannel remote sensing images in the case of signal-dependent noise present in component images. Three approaches to filtering of multichannel images for the considered noise model are analysed, all based on discrete cosine transform in blocks. The study is carried out not only in terms of conventional efficiency metrics used in filtering (MSE) but also in terms of multichannel data classification accuracy (probability of correct classification, confusion matrix). The proposed classification system combines the pre-processing stage where a DCT-based filter processes the blocks of the multichannel remote sensing image and the classification stage. Two modern classifiers are employed, radial basis function neural network and support vector machines. Simulations are carried out for three-channel image of Landsat TM sensor. Different cases of learning are considered: using noise-free samples of the test multichannel image, the noisy multichannel image and the pre-filtered one. It is shown that the use of the pre-filtered image for training produces better classification in comparison to the case of learning for the noisy image. It is demonstrated that the best results for both groups of quantitative criteria are provided if a proposed 3D discrete cosine transform filter equipped by variance stabilizing transform is applied. The classification results obtained for data pre-filtered in different ways are in agreement for both considered classifiers. Comparison of classifier performance is carried out as well. The radial basis neural network classifier is less sensitive to noise in original images, but after pre-filtering the performance of both classifiers is approximately the same.