Implementing Transfer Learning for Mitotic Cell Detection

The primary objective of this project is to use a neural network (deep learning) model that will be trained on datasets of human cells in mitosis and then apply it on animal cells using transfer learning techniques. The purpose of this project is to speed up the process for the pathologist to detect mitotic activity for cancer diagnosis and determine transfer learning techniques that will aid in predicting mitotic activity in animal cells. This information will prove to be useful for correct diagnosis of cancer and reduce potential errors of detecting mitotic cells. Instead of acquiring the highly meticulous task of the labelled data, transfer learning can produce promising results by reusing the learned features from human datasets and applying the learned knowledge to the datasets of the animal cells. This project proposes to develop a higher detection accuracy with our framework of transfer learning and optimize the deep learning model to produce the desired output of detecting mitotic cells in animals with the limited amount of training data. Transfer learning techniques will be aimed to improve the performance of learning in other domains and reduce the cost of the expensive labeled data

Computer Numerical Controlled (CNC) machining for Rapid Manufacturing Processes

The trends of rapid manufacturing (RM) have influenced numerous developments of technologies mainly in additive processes. However, the material compatibility and accuracy problems of additive techniques have limited the ability to manufacture end-user products. More established manufacturing methods such as Computer Numerical Controlled (CNC) machining can be adapted for RM under some circumstances. The use of a 3-axis CNC milling machine with an indexing device increases tool accessibility and overcomes most of the process constraints. However, more work is required to enhance the application of CNC for RM, and this thesis focuses on the improvement of roughing and finishing operations and the integration of cutting tools in CNC machining to make it viable for RM applications. The purpose of this research is to further adapt CNC machining to rapid manufacturing, and it is believed that implementing the suggested approaches will speed up production, enhance part quality and make the process more suitable for RM. A feasible approach to improving roughing operations is investigated through the adoption of different cutting orientations. Simulation analyses are performed to manipulate the values of the orientations and to generate estimated cutting times. An orientations set with minimum machining time is selected to execute roughing processes. Further development is carried out to integrate different tool geometries; flat and ball nose end mill in the finishing processes. A surface classification method is formulated to assist the integration and to define the cutting regions. To realise a rapid machining system, the advancement of Computer Aided Manufacturing (CAM) is exploited. This allows CNC process planning to be handled through customised programming codes. The findings from simulation studies are supported by the machining experiment results. First, roughing through four independent orientations minimized the cutting time and prevents any susceptibility to tool failure. Secondly, the integration of end mill tools improves surface quality of the machined parts. Lastly, the process planning programs manage to control the simulation analyses and construct machining operations effectively

Study on the Morphology and Fiber Properties of Nanoclay Added Polyvinyl Alcohol (PVA) Nanofibrous Mats: Effect of Mechanical Dispersion

In this study, polyvinyl alcohol (PVA) polymer and Cloisite 15A, a modified form of organo Montmorillonite nanoclay, are used to produce nanofibrous mats via electrospinning technique. Pure PVA nanofibrous mats from mechanically stirred polymeric solutions at 8, 10 and 12 wt % PVA percents; and nanoclay added PVA nanofibrous mat samples are produced at increased nanoclay weight/ polymer weight ratios (1/13, 1/11, 1/9 and 1/6) using several mechanically stirred nanoclay-PVA solutions at various proportions of nanoclay and PVA polymer wt % in solutions. The viscosities, surface tensions and electrical conductivities of solutions were measured. FESEM (Field Emission Scanning Electron Microscopy) analysis, fiber diameter distribution with Image J software analysis and tensile testing was applied to nanofibrous samples. Increased polymer concentration led to bead-free nanofibrous PVA mats. EDX analysis approved nanoclay is present in samples produced from nanoclay added PVA solutions. Mechanical stirring for nanoclay dispersion enabled smooth nanofibrous structures only in low (1/13) nanoclay weight/ polymer weight ratios and showed very little tensile increase from 1 wt % clay loading to 2 wt % addition. A direct increase in tensile strength wasn’t achieved with nanoclay content increase in PVA nanofibrous mats; this might be due to the effect of poor nanoclay distribution adversely affecting tensile results. Morphological analysis proved that nanofibrous structures were far away from smooth fiber structures as they transformed from smooth nanofibers into non-uniform fibrous structures at increased nanoclay weight/ polymer weight ratios in nanoclay added PVA samples. Keywords: nanofibrous mat, electrospinning, polyvinyl alcohol (PVA), nanoclay, mechanical dispersion DOI: 10.7176/CPER/62-08 Publication date: May 30th 202

Untersuchungen zur Effizienz von Aflibercept, Ranibizumab und Bevacizumab bei der feuchten Form der altersbedingten Makuladegeneration mit einem in vitro Organkulturmodell

Die feuchte exsudative Form der altersbedingten Makuladegeneration (AMD) ist die häufigste Erblindungsursache in der westlichen Welt. Im Rahmen des Pathomechanismus dieser Erkrankung spielt der Vascular Endothelial Growth Factor (VEGF) eine zentrale Rolle. Durch eine erhöhte Ausschüttung von VEGF durch das RPE kommt es zum Auswachsen von Kapillargefäßen. Diese choroideale Neovaskularisation (CNV) führt im Endstadium zum zentralen Visusverlust. Bei der Behandlung der CNV im Rahmen der AMD ist die pharmakologische Neutralisierung der erhöhten VEGF-Konzentration die Methode der ersten Wahl. Aktuell werden in der Klinik die drei anti-VEGF Präparate Bevacizumab, Ranibizumab und Aflibercept verwendet. In der vorliegenden Arbeit wurde die Wirksamkeit der VEGF-Inhibitoren in einem in vitro Organkulturmodell verglichen. Hierzu wurden RPE/Choroidea-Organkulturen aus frisch geschlachteten Schweinen verwendet.The wet exudative form of age-related macular degeneration (AMD) is the most common cause of blindness in the Western world. The vascular endothelial growth factor (VEGF) plays a central role in the pathomechanism of this disease. An increased release of VEGF by the RPE leads to the outgrowth of capillaries. This choroidal neovascularization (CNV) leads to central vision loss in the terminal stage. In the treatment of CNV in the context of AMD, the pharmacological neutralization of the increased VEGF concentration is the method of first choice. Currently, the clinic uses the three anti-VEGF preparations bevacizumab, ranibizumab and aflibercept. In the present work, the efficacy of VEGF inhibitors in an in vitro organ culture model was compared. For this purpose, RPE / Choroidea organ cultures were used from freshly slaughtered pigs

End mill tools integration in CNC machining for rapid manufacturing processes: simulation studies

Computer Numerical Controlled (CNC) machining has been recognized as a manufacturing process that is capable of producing metal parts with high precision and reliable quality, whereas many additive manufacturing methods are less capable in these respects. The introduction of a new layer removal methodology that utilizes an indexing device to clamp the workpiece can be used to extend CNC applications into the realm of rapid manufacturing (CNC-RM) processes. This study aims to improve the implementation of CNC machining for RM by formulating a distinct approach to integrate end mill tools during finishing processes. A main objective is to enhance process efficiency by minimizing the stair-casing effect of layer removal so as to improve the quality of machined parts. In order to achieve this, different types of end mill tools are introduced to cater for specific part surfaces during finishing operations. Virtual machining simulations are executed to verify the method and the implications. The findings indicate the advantages of the approach in terms of cutting time and excess volume left on the parts. It is shown that using different tools for finishing operations will improve the capabilities of CNC machining for rapid manufacturing applications

Cutting tools in finishing operations for CNC rapid manufacturing processes: simulation studies

CNC machining has been widely used in producing metal parts with high accuracy and reliable quality. A distinct process planning approach that utilizes an indexing device to hold the workpiece has extended CNC applications into the realm of rapid manufacturing (CNC-RM) processes. This study improves the implementation of this technology by providing a methodology for integrating the tools into finishing processes. It aims to enhance the process efficiency by minimizing the stair-casing effect of layer removal and so improve the quality of machined parts. In order to achieve this, finishing operations are executed using different types of end mill tools to cater for specific surfaces. Simulations are carried out to verify the method and implications. The findings indicate the advantages of the approach in terms of cutting time and the minimisation of excess volumes left on parts. Using different cutters for finish cuts improves the capabilities of CNC machining in rapid manufacturing applications

RSS-based wireless LAN indoor localization and tracking using deep architectures

Wireless Local Area Network (WLAN) positioning is a challenging task indoors due to environmental constraints and the unpredictable behavior of signal propagation, even at a fixed location. The aim of this work is to develop deep learning-based approaches for indoor localization and tracking by utilizing Received Signal Strength (RSS). The study proposes Multi-Layer Perceptron (MLP), One and Two Dimensional Convolutional Neural Networks (1D CNN and 2D CNN), and Long Short Term Memory (LSTM) deep networks architectures for WLAN indoor positioning based on the data obtained by actual RSS measurements from an existing WLAN infrastructure in a mobile user scenario. The results, using different types of deep architectures including MLP, CNNs, and LSTMs with existing WLAN algorithms, are presented. The Root Mean Square Error (RMSE) is used as the assessment criterion. The proposed LSTM Model 2 achieved a dynamic positioning RMSE error of 1.73 m, which outperforms probabilistic WLAN algorithms such as Memoryless Positioning (RMSE: 10.35 m) and Nonparametric Information (NI) filter with variable acceleration (RMSE: 5.2 m) under the same experiment environment.ECSEL Joint Undertaking ; European Union's H2020 Framework Programme (H2020/2014-2020) Grant ; National Authority TUBITA

Optimization of roughing operations in CNC machining for rapid manufacturing processes

This paper presents a method for optimizing roughing operations in CNC machining, particularly for parts production through a subtractive rapid manufacturing process. The overall objective is to utilize the characteristics of CNC machining (rapid removal rates, suitability for a wide range of materials and precision) whilst obtaining some of the benefits of additive manufacturing (shape flexibility and reduction in process planning effort). The roughing operation in machining is primarily used to remove the bulk material and to approximately shape the workpiece towards the finished form. The manufacturing process described, utilizes a three-axis CNC machine with an indexable fourth axis device that is used to hold and rotate the workpiece. The method uses multiple approaches in roughing operations that differ in the number of orientations and the angles of the orientations. Most of the machining parameters are generalized throughout the process to allow some automation in generating the machining programme. The performance of each of the approaches is evaluated based on the lowest machining time to produce the part

Cutting orientations for non-complex parts in 4axis machining

The application of Computer Numerically Controlled (CNC) machining for Rapid Manufacturing processes (CNC-RM) exploits the innate potential of 4th axis machining. The use of an indexer allows the workpiece to be rotated to various orientations which directly increased the region accessible to the cutting tool. However, in order to avoid thin webs and preserve tool life, cutting must be executed with a minimum of three orientations even for geometrically simple parts. Recent findings have suggested the separation of cutting orientations into roughing and finishing operations. Thus, the selection of orientations in finishing processes becomes more flexible and independent. This study was conducted to identify the effects of using a minimum of two cutting orientations in finishing operations for CNC-RM applications. This method is only applicable for non-complex parts where all the features can be machined from two directions. The results of the study illustrate the positive effects of minimizing the number of orientations. Despite improvement in machining operations, the complexity in defining the cutting orientations was also reduced

Rapid process planning in CNC machining for rapid manufacturing applications

Process planning is an important component in Computer Numerical Control (CNC) machining and directly influences the efficiency of cutting operations. However the planning task is highly dependent on the user’s experience and is usually considered as a manual process. This paper seeks to remedy these problems by developing a tool to assist in executing the process planning task in CNC machining for rapid manufacturing applications. An advanced tool in Computer Aided Manufacturing (CAM) systems is exploited to record and generate programming code for instructions used to construct the operations. The code is then modified and integrated into the independent Graphical User Interface (GUI) to execute the process planning tasks within the CAM systems. Consequently, a customized program is developed and is capable of building the machining operations for all kinds of parts. The time spent for process planning is minimized and at the same time planning complexity that is highly depend on the user’s experience is reduced