Publications
Seeking to Reduce Contamination in Production Lines (Converting Machines) |
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We are seeking to reduce contamination in our production lines (converting machines). The specific machines use diverse web materials (mainly non-woven based) to produce our products. The materials come to our machines in a planetary roll form. Those rolls would be unwound and conveyed through the converting processes (combining, cutting…) to form final products. Within this process, the web materials release different sources of contamination (e.g. dust &/or fibers) causing accumulation of contamination in all places of the machine where it can settle. With the late changes of materials, we have seen a substantial increase in contamination. As a result, we need to move cleaning times from 8 hour intervals (10 minute cleaning with 2 operators) to less than 6 hour intervals (>15min cleaning with 4 people). In order to maintain operability standards and productivity, we are seeking methods to return to 8 hour cleaning intervals. |
Seeking existing market solutions targeted towards crawling insects |
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The issue of crawling insects in homes has been an ongoing issue. The popular types of crawling insects causing problems have been ants and cockroaches. The search will focus on existing market solutions targeted towards crawling insects such as ants and cockroaches (other types of crawling insects are in scope i.e., bed bugs). |
Seeking natural colors for foods and beverages |
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PepsiCo is evaluating different natural color ingredients and technologies to replace Yellow #5, Yellow #6, Red #40, and Blue #1 for multiple food and beverage brands in order to address consumer demand. Specific challenges are in the Red #40 (food) and Blue #1 (food & beverage) replacers. |
Multipurpose stamped conductive graphene nano films |
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A new method for the fabrication and easy patterning of flexible exfoliated graphene nano films which can work as electrochemical electrodes for different applications. |
Technology to Modify Alcohol Content in Alcoholic Beverages |
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The company has developed an innovative process which removes only the alcohol while preserving all other flavours in beer. The patented technology is currently in system prototype state (TRL 6) and the company is keen to partner with global breweries and other global beverage companies to develop low-alcoholic or non-alcoholic beverages. Shifting beverage consumption patterns along with rising preference for low liquor content beverages are the key factor propelling non-alcoholic beer demand. Increasing health awareness among consumers towards the harmful effects of liquor coupled with changing lifestyle is expected to propel industry growth. Considerable shift of young individuals to purchase a variety of alcohol-free or low alcohol variants is expected to drive product penetration. The changing demographic trends of growing Muslim population has also provided a positive outlook for non-alcoholic beer market. But TASTE is still a major issue which has held back a real boom of non-alcoholic beer. Market shares could easily rise to 20-25% of total sales volume from today's 3-4%, if the right technology comes along. Current biological or physical processes so far used to remove or prevent alcohol often also remove taste-related flavours or alter the flavour profile of the finished product. |
Image processing method for glaucoma detection and computer program |
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We have developed a new algorithm for ordering anterior chamber OCT images in such a way that it is possible to classify them, in a fully unsupervised manner, in meaningful groups according to relevant features. We have tested the algorithm with a large set of images classified by two expert ophthalmologists, and with a larger set of annotated images. We have verified that the separation in the different classes defined by the ophthalmologists (closed, narrow, open, and wide open_ figure 6) is similar when using the manually extracted features, or when using the features that are returned by the unsupervised algorithm (View figures). Therefore, the abstract features generated by the algorithm provide novel tools for assessing OCT images of the anterior chamber. They can be used for direct classification of the images and, furthermore, they can be linked to established quantities used for characterizing diseased eyes (like chamber depth, iris-corneal angle) resulting in an automatic detection system. As the algorithm is fully unsupervised, it can be easily automated and set up in OCT imaging systems to aid technicians and doctors in an early diagnosis. The two main advantages of the algorithm demonstrated here over previous works are that it doesn’t need any ground truth or gold standard for training, and it does not rely on specific landmarks; thus, it can analyze images in which relevant landmarks are not visible or not easy to locate. |
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