Influence of Cutting Conditions on Tool Life, Tool Wear and Surface Finish in the Face Milling Process

The main goal of this work is to study the influence of cutting conditions - cutting speed, feed velocity and feed per tooth - on tool life and surface finish of the workpiece in the face milling of flat surfaces. Aiming to achieve this goal, several milling experiments were carried out with different cutting speeds, feed velocities and feeds per tooth. In the first phase of the experiments, cutting speed was varied without varying feed velocity, which caused a variation in feed per tooth. In the second phase of the experiments, cutting speed and feed velocity were varied in such a way that feed per tooth was kept constant. Tool flank wear and surface roughness of the workpiece were measured as cutting time elapsed. The main conclusions of this work are that a) cutting speed has a strong influence on tool life, regardless of whether feed velocity or feed per tooth varies and b) an increase in surface roughness of the workpiece is not closely related to an increase in wear of the primary cutting edge.

Hot tool temperature analysis though infrared images

Textile manufacture occupies a prominent place in the national economy. Because of its importance researches have been made on the development of new materials, equipment and methods used in the production process. The cutting of textiles starts in the basic stage, to be followed by the process of the making of clothes and other articles. In the hot cutting of fabric, one of the variables of great importance in the control of the process is the contact temperature between the tool and the fabric. This work presents a technique for the measurement of the temperature based on the processing of infrared images. With this purpose, it was developed a system which is composed of an infrared camera, a framegrabber PC board and a software which analyses the punctual temperature in the cut area enabling the operator to achieve the necessary control of other variables involved in the process.

Indoor Localization Solutions for a Marine Industry Augmented Reality Tool

In this report are described means for indoor localization in special, challenging circum-stances in marine industry. The work has been carried out in MARIN project, where a tool based on mobile augmented reality technologies for marine industry is developed. The tool can be used for various inspection and documentation tasks and it is aimed for improving the efficiency in design and construction work by offering the possibility to visualize the newest 3D-CAD model in real environment. Indoor localization is needed to support the system in initialization of the accurate camera pose calculation and auto-matically finding the right location in the 3D-CAD model. The suitability of each indoor localization method to the specific environment and circumstances is evaluated.

“Development work thesis” as a tool for continuing professional education

Julkaisumaa: 158 TW TWN Taiwan

Diffusion Tensor Imaging as a Diagnostic and Research Tool: A Study on Preterm Infants

Diffusion tensor imaging (DTI) is an advanced magnetic resonance imaging (MRI) technique. DTI is based on free thermal motion (diffusion) of water molecules. The properties of diffusion can be represented using parameters such as fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity, which are calculated from DTI data. These parameters can be used to study the microstructure in fibrous structure such as brain white matter. The aim of this study was to investigate the reproducibility of region-of-interest (ROI) analysis and determine associations between white matter integrity and antenatal and early postnatal growth at term age using DTI. Antenatal growth was studied using both the ROI and tract-based spatial statistics (TBSS) method and postnatal growth using only the TBSS method. The infants included to this study were born below 32 gestational weeks or birth weight less than 1,501 g and imaged with a 1.5 T MRI system at term age. Total number of 132 infants met the inclusion criteria between June 2004 and December 2006. Due to exclusion criteria, a total of 76 preterm infants (ROI) and 36 preterm infants (TBSS) were accepted to this study. The ROI analysis was quite reproducible at term age. Reproducibility varied between white matter structures and diffusion parameters. Normal antenatal growth was positively associated with white matter maturation at term age. The ROI analysis showed associations only in the corpus callosum. Whereas, TBSS revealed associations in several brain white matter areas. Infants with normal antenatal growth showed more mature white matter compared to small for gestational age infants. The gestational age at birth had no significant association with white matter maturation at term age. It was observed that good early postnatal growth associated negatively with white matter maturation at term age. Growth-restricted infants seemed to have delayed brain maturation that was not fully compensated at term, despite catchup growth.

Perspectives for using light quality knowledge as an advanced ecophysiological weed management tool

The current knowledge of light quality effects on plant morphogenesis and development represents a new era of understanding on how plant communities perceive and adjust to available resources. The most important consequences of light quality cues, often mediated by decreasing in red far-red ratios with respect to the spectral composition of incident sunlight radiation, affecting weed-crop interaction are the increased plant height and shoot to root ratio in anticipation of competition by light quantity, water or nutrients. Although the concepts related to light quality have been extensively studied and several basic process of this phenomenon are well known, little applications of photomorphogenic signaling currently are related to agricultural problems or weed management. The objectives of this review are to describe how light quality change can be a triggering factor of interspecific interference responses, to analyze how this phenomenon can be used to predict weed interference, to reevaluate the critical periods of interference concept, and to discuss its potential contribution towards developing more weed competitive crop varieties. Knowledge on light quality responses involved in plant sensing of interspecific competition could be used to identify red/far-red threshold values, indicating when weed control should be started. Light quality alterations by weeds can affect grain crop development mainly in high yielding fields. Unlike the traditional concept or the critical period of competition, light quality mediated interference implies that the critical period for weed control could start before the effects of direct resource (water, nutrients and available light) limitation actually occur. The variability in light quality responses among crop genotypes and the identification of mutants insensitive to light quality effects indicate that this characteristic can be selected or modified to develop cultivars with enhanced interspecific interference ability. Knowledge on light quality-elicited responses represents a new possibility to understand the underlying biology of interspecific interference, and could be used in the development of new weed management technologies.

Reflectance indices as a diagnostic tool for weed control performed by multipurpose equipment in precision agriculture

Several tools of precision agriculture have been developed for specific uses. However, this specificity may hinder the implementation of precision agriculture due to an increasing in costs and operational complexity. The use of vegetation index sensors which are traditionally developed for crop fertilization, for site-specific weed management can provide multiple utilizations of these sensors and result in the optimization of precision agriculture. The aim of this study was to evaluate the relationship between reflectance indices of weeds obtained by the GreenSeekerTM sensor and conventional parameters used for weed interference quantification. Two experiments were conducted with soybean and corn by establishing a gradient of weed interference through the use of pre- and post-emergence herbicides. The weed quantification was evaluated by the normalized difference vegetation index (NDVI) and the ratio of red to near infrared (Red/NIR) obtained using the GreenSeekerTM sensor, the visual weed control, the weed dry matter, and digital photographs, which supplied information about the leaf area coverage proportions of weed and straw. The weed leaf coverage obtained using digital photography was highly associated with the NDVI (r = 0.78) and the Red/NIR (r = -0.74). The weed dry matter also positively correlated with the NDVI obtained in 1 m linear (r = 0.66). The results indicated that the GreenSeekerTM sensor originally used for crop fertilization could also be used to obtain reflectance indices in the area between rows of crops to support decision-making programs for weed control.

OCR Correction Tool for Linguistic Corpora

We introduce a new tool for correcting OCR errors of materials in a repository of cultural materials. The poster is aimed to all who are interested in digital humanities and who might find our tool useful. The poster will focus on the OCR correction tool and on the background processes. We have started a project on materials published in Finno-Ugric languages in the Soviet Union in the 1920s and 1930s. The materials are digitised in Russia. As they arrive, we publish them in DSpace (fennougrica.kansalliskirjasto.fi). For research purposes, the results of the OCR must be corrected manually. For this we have built a new tool. Although similar tools exist, we found in-house development necessary in order to serve the researchers' needs. The tool enables exporting the corrected text as required by the researchers. It makes it possible to distribute the correction tasks and their supervision. After a supervisor has approved a text as finalised, the new version of the work will replace the old one in DSpace. The project has - benefitted the small language communities, - opened channels for cooperation in Russia. - increased our capabilities in digital humanities. The OCR correction tool will be available to others.

Glyphosate as a tool to produce shikimic acid in plants

Oseltamivir phosphate is a potent viral inhibitor produced from shikimic acid extracted from seeds of Ilicium verum, the most important natural source. With the site of action 5-enolpyruvylshikimate-3-phosphate synthase (EPSP), glyphosate is the only compound capable of inhibiting its activity with the consequent accumulation of shikimic acid in plants. Corn and soybean plants were sprayed with reduced rates of glyphosate (0.0 to 230.4 g a.i. ha¹) and shikimic acid content in the dry mass was determined by HPLC 3, 7 and 10 days after application. Results showed shikimic acid accumulation in dry mass with increases of up to 969% in corn and 33,000% on soybeans, with peak concentrations 3 days after treatment (DAT). Industrial feasibility for shikimic acid production, combined with favorable climatic conditions for growing corn and soybean in virtually all over Brazil, favor the use of reduced rates of glyphosate in shikimic acid biosynthesis, with potential for use as an inducer in exploration of alternative sources for production of oseltamivir phosphate with low environmental impact.

Interoperability specifications and an automatic validation tool as a key factor for the support of a repository ecosystem

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

OCR Correction Tool for Linguistic Corpora

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

HIMALDOC: A Tool for a Regional Open Repository on Sustainable Mountain Development Issues in the Hindu Kush Himalaya

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

The Pay-Off Method as a Tool for Evaluating the Risk and Profitability of Public Real Estate Investments

Real option valuation, in particular the fuzzy pay-off method, has proven to be useful in defining risk and visualizing imprecision of investments in various industry applications. This study examines whether the evaluation of risk and profitability for public real estate investments can be improved by using real option methodology. Firstly, the context of real option valuation in the real estate industry is examined. Further, an empirical case study is performed on 30 real estate investments of a Finnish government enterprise in order to determine whether the presently used investment analysis system can be complemented by the pay-off method. Despite challenges in the application of the pay-off method to the case company’s large investment base, real option valuation is found to create additional value and facilitate more robust risk analysis in public real estate applications.

Automatic traffic sign inventory- and condition analysis

This thesis researches automatic traffic sign inventory and condition analysis using machine vision and pattern recognition methods. Automatic traffic sign inventory and condition analysis can be used to more efficient road maintenance, improving the maintenance processes, and to enable intelligent driving systems. Automatic traffic sign detection and classification has been researched before from the viewpoint of self-driving vehicles, driver assistance systems, and the use of signs in mapping services. Machine vision based inventory of traffic signs consists of detection, classification, localization, and condition analysis of traffic signs. The produced machine vision system performance is estimated with three datasets, from which two of have been been collected for this thesis. Based on the experiments almost all traffic signs can be detected, classified, and located and their condition analysed. In future, the inventory system performance has to be verified in challenging conditions and the system has to be pilot tested.

Dual light barrier method for six degrees of freedom tool center point calibration of an industrial robot

Tool center point calibration is a known problem in industrial robotics. The major focus of academic research is to enhance the accuracy and repeatability of next generation robots. However, operators of currently available robots are working within the limits of the robot´s repeatability and require calibration methods suitable for these basic applications. This study was conducted in association with Stresstech Oy, which provides solutions for manufacturing quality control. Their sensor, based on the Barkhausen noise effect, requires accurate positioning. The accuracy requirement admits a tool center point calibration problem if measurements are executed with an industrial robot. Multiple possibilities are available in the market for automatic tool center point calibration. Manufacturers provide customized calibrators to most robot types and tools. With the handmade sensors and multiple robot types that Stresstech uses, this would require great deal of labor. This thesis introduces a calibration method that is suitable for all robots which have two digital input ports free. It functions with the traditional method of using a light barrier to detect the tool in the robot coordinate system. However, this method utilizes two parallel light barriers to simultaneously measure and detect the center axis of the tool. Rotations about two axes are defined with the center axis. The last rotation about the Z-axis is calculated for tools that have different width of X- and Y-axes. The results indicate that this method is suitable for calibrating the geometric tool center point of a Barkhausen noise sensor. In the repeatability tests, a standard deviation inside robot repeatability was acquired. The Barkhausen noise signal was also evaluated after recalibration and the results indicate correct calibration. However, future studies should be conducted using a more accurate manipulator, since the method employs the robot itself as a measuring device.