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DropConnect (the generalization of Dropout) is a very simple regularization technique that was introduced a few years ago and has become extremely popular because of its simplicity and effectiveness. In this thesis, a suitable architecture for applying DropConnect to Learning Vector Quantization networks is proposed along with a reference implementation and experimental results. Inmany classification tasks, the uncertainty of themodel is a vital piece of information for experts. Methods to extract the uncertainty and stability using DropConnect are also proposed and the corresponding experimental results are documented.
The subject of the following paper is the mental well-being of employees at their work and how the leader can improve this well-being using positive psychology. The paper is compilatory in nature because it uses research and literature of experts to analyse how employee mental well-being can be further stimulated. The expert literature is used to present tools, but also to demonstrate the effectiveness of these tools through real-life case studies and evidence. The paper wishes to inform persons, leaders, and entire organizations how positive psychology can be beneficial to organizational members’ well-being in the long term. Using a compilation of positive psychology literature and reallife case studies’ analysis, the informative purpose of the thesis can be achieved.
This thesis work is focusing on the optimization and improvement of IP network and IP transit operations and strategy as well as service offerings. Therefore, this thesis tries to give suggestions at different areas of engineering, business, strategy and operational contexts. This thesis is written in English, as this topic itself is mainly handled in English language too. The first part will try to identify and evaluate methods which are helpful to improve the practical work which will be focused in the second part of this work.
Internationalization and business expansion appear to be the most challenging processes in business conduction today. Every step of the foreign market entry process and overseas operations establishment is full of obvious risks and hidden pitfalls. Theoretical background, multiplied with the vital practice, is playing the key role in such a complicated business process; such information can be used as a guideline by further market entrants and players. At present, Germany with its well-developed engineering industry represents a broad space for research of internationalization process in its different forms, as well as can show both successful and negative results of foreign market entries.
Object detection and classification is active field of research inmachine learning and computervision. Depending on the application there are different limitations to adjust to, but also possibilities to take advantage of. In my thesis, We focus on classification and detection of video sequence during night-time and the proposed method is robust since it does use image thresholding [8] which is commonly use in other methods and the thesis uses histograms of oriented gradients (HOG) [37] as features and support vector machine (SVM) [74] as classifier. It is of great importance that the extracted features from the images should be robust and distinct enough to help the classifier distinguish between high-beam and a low-beam. The classifier is part of the object detection which predicts whether or not a testing image matches one group or the other. In our case that is predicting whether or not an image belongs to high or low-beam sequence.
In the following study the properties of the superabsorbent polymer Broadleaf P4 were investigated according to the aim to apply that polymer within constructed wetlands. The application of the polymer in constructed wetlands shall result in an improvement of the removal of pesticides. For that the polymer was given into lab-scale wetlands together with pumice and were compared to a control wetland, which was filled with gravel. The wetlands were running for several weeks in which the nutrient removal was recorded. The polymer was also tested according to its property to adsorb the pesticides before adding the pesticides to the wetland beds.
FUSO is one of the Japanese leading manufacturing of trucks and buses in the world and also it is an integral part of Daimler AG. Being a large manufacturer in trucks and buses, Fuso faces some marketing issues due to corrosion issues. Corrosion is one of the major issue to breakdown or damage the performance of the vehicles. To encounter this issue, FUSO initiated new project and called as “Anti-Corrosion Project”. The main mission of this project is to improve the corrosion resistivity or performance of the metal parts. Currently FUSO has almost 70 percent of parts which lies under Grade-III i.e. lesser than the one year corrosion resistivity.
In this project, the corrosion issues are collected by different types of audits like from customer as well as from taking two years old vehicle in worst conditions. Listed corrosion issues further investigated for current specification and requested for new proposal from supplier. Then the proposed solution is internally estimate the cost and make negotiation with the supplier. Later it’s forwarded to meeting with top management for approval. In case of higher corrosion specification, parts are taken from production line and tested in material lab which is available in FUSO. At last, the approved proposal is requested to release the drawing change and further the new proposal will be implemented. Entire project it should be coordinate with all different departments and working with teams gives more deep knowledge about the cause of issues.
With this project, parallel focused on the shop floor developments in return parts management area. FUSO is also responsible for the after sale services. In other words, FUSO provides warranty for the parts which breakdown within three years. Breakdown parts are directly delivered by the customers through dealers for warranty claim, so these parts called Warranty Part Investigation (WPI) parts. Sometimes customer wants to know the cause of the breakdown even though warranty has expired, in this case company will investigate the cause but they don’t provide the warranty. These kind of parts known as Product Quality Report (PQR) parts.
Company has a different shop floor for return parts and these parts are directly received by the company. RPM has four processes i.e. inwarding, pre-analysis, investigation and dispatch or scrap.
Usually, company used to get 30-50 parts per day, recently they decided to receive all the breakdown parts. Hence, it results in increasing the delay of inwarding and other processes. To solve this, standard layout and process are constructed. And, one of the main reasons for inward delay is higher documentation which is basically not required. These are converted into automation or digitalize work. Improvements are done using the lean manufacturing project methodology which results in more inward of failure parts and less inventory.
Many companies use machine learning techniques to support decision-making and automate business processes by learning from the data that they have. In this thesis we investigate the theory behind the most widely used in practice machine learning algorithms for solving classification and regression problems.
In particular, the following algorithms were chosen for the classification problem: Logistic Regression, Decision Trees, Random Forest, Support Vector Machine (SVM), Learning Vector Quantization (LVQ). As for the regression problem, Decision Trees, Random Forest and Gradient Boosted Tree were used. We then apply those algorithms to real company data and compare their performances and results.
The application described in this thesis has been created, built and designed to help nurses or any medical personnel all around the world in being able to access a real-time database to store patient records like Patient Name, Patient ID, Patient Age and Date of Birth, and the Symptoms that the patient is experiencing. A real-time database is a live database where all changes made to it are reflected across all devices accessing it. This application will be beneficial especially in countries where access to a computer or medical equipment is not always possible. A phone is always ready use and at the reach of the hand, users of this application will always be able to access the data at any given time and place. We will be able to add a new patient or search for existing patients. In addition, this application allows us to take RAW medical images that can be used to identify anomalies in the blood sample. RAW images are important for this application because they’re uncompressed, which means, they do not lose any quality or details. The users of this application are the medical personnel that will be taking care of the patients. These users will have to create a profile on the database in order to use the application, since their data, like user ID, will be used in order to control the behaviour of the data retrieved and stored. We will also discuss the current and future features of this application, as well as, the benefits of this application when it comes to the medical personnel, as well as patients. Finally, we will also go
over the implementation of such application from a hardware perspective, as well as a software one.