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For a holistic assessment of the interaction between the human body and tight fitted clothing, it is necessary to consider the mechanical properties of the body. Default avatars in CAD software are usually solid and do not take this interaction into account. For this purpose, a solid avatar is converted to a deformable one by using the soft body physics implementation in the simulation program Blender. The fit of a 3D garment on both avatars are compared, which allows a first evaluation of the differences between these approaches.
Hochschulabsolventen sind für Unternehmen eine der wichtigsten Quellen für die Nachwuchsrekrutierung. Doch wie erreichen Sie die jungen Studenten am Besten? Eine bloße Ausschreibung einer Stelle auf der Unternehmenswebseite reicht nicht mehr aus. Wir zeigen Ihnen, wie Sie bereits vor dem Bewerbungsprozess in der Lebenswirklichkeit (Relevant Set) der Studierenden präsent werden, um überhaupt als Arbeitgeber in Betracht gezogen zu werden.
Three established test methods employed for evaluating the abrasion or wear resistance of textile materials were compared to gain deeper insight into the specific damaging mechanisms to better understand a possible comparability of the results of the different tests. The knowledge of these mechanisms is necessary for a systematic development of finishing agents improving the wear resistance of textiles. Martindale, Schopper, and Einlehner tests were used to analyze two different fabrics made of natural (cotton) or synthetic (polyethylene terephthalate) fibers, respectively. Samples were investigated by digital microscopy and scanning electron microscopy to visualize the damage. Damage symptoms are compared and discussed with respect to differences in the damaging mechanisms.
The following paper is dealing with the issue on which actual consumer lifestyle segmentation methods there are for particular European countries and accordingly for Europe as a whole. This is important for corporations to be able to place their products accurately by a consumer orientated marketing concerning the constant change of values and minds. Researching current literature, internet sources and documents, the state of the science is presented by a detailed description of the most popular lifestyle segmentation methods used in European countries. In addition to that, these instruments are discussed individually and then compared to each other. All instruments, the Sinus-Milieus, Euro-Socio-Styles, Roper-Consumer-Styles, RISC and Mosaic, are serving the same purpose even so they differ pretty much from each other. Each market research company has its own method to generate their model just as different segments and definitions for them. Furthermore every segmentation method is illustrated in a different way. This paper demonstrates all these instruments in detail and shows its advantages and disadvantages. Summing up literature research concerning the main research question, there are several models segmenting consumers in different lifestyle groups for e.g. in Germany, France or Great Britain, but still less models referring to the entire European market.
Like many others, fashion companies have to deal with a global and very competitive environment. Thus companies rely on accurate sales forecasts - as key success factor of an efficient supply chain management. However, forecasters have to take into account some specificities of the fashion industry. To respond to these constraints, a variety of different forecasting methods exists, including new, computer-based predictive analytics. After the evaluation of different methods, their application to the fashion industry is investigated through semi structured expert interviews. Despite several benefits predictive analytics is not yet frequently used in practice. This research does not only reflect an industry profile, but also gives important insights about the future potential and obstacles of predictive analytics.
Cotton contamination by honeydew is considered one of the significant problems for quality in textiles as it causes stickiness during manufacturing. Therefore, millions of dollars in losses are attributed to honeydew contamination each year. This work presents the use of UV hyperspectral imaging (225–300 nm) to characterize honeydew contamination on raw cotton samples. As reference samples, cotton samples were soaked in solutions containing sugar and proteins at different concentrations to mimic honeydew. Multivariate techniques such as a principal component analysis (PCA) and partial least squares regression (PLS-R) were used to predict and classify the amount of honeydew at each pixel of a hyperspectral image of raw cotton samples. The results show that the PCA model was able to differentiate cotton samples based on their sugar concentrations. The first two principal components (PCs) explain nearly 91.0% of the total variance. A PLS-R model was built, showing a performance with a coefficient of determination for the validation (R2cv) = 0.91 and root mean square error of cross-validation (RMSECV) = 0.036 g. This PLS-R model was able to predict the honeydew content in grams on raw cotton samples for each pixel. In conclusion, UV hyperspectral imaging, in combination with multivariate data analysis, shows high potential for quality control in textiles.
Patterns are virtually simulated in 3D CAD programs before production to check the fit. However, achieving lifelike representations of human avatars, especially regarding soft tissue dynamics, remains challenging. This is mainly since conventional avatars in garment CAD programs are simulated with a continuous hard surface and not corresponding to the human physical and mechanical body properties of soft tissue. In the real world, the human body’s natural shape is affected by the contact pressure of tight-fitting textiles. To verify the fit of a simulated garment, the interactions between the individual body shape and the garment must be considered. This paper introduces an innovative approach to digitising the softness of human tissue using 4D scanning technology. The primary objective of this research is to explore the interactions between tissue softness and different compression levels of apparel, exerting pressure on the tissue to capture the changes in the natural shape. Therefore, to generate data and model an avatar with soft body physics, it is essential to capture the deform ability and elasticity of the soft tissue and map it into the modification options for a simulation. To aim this, various methods from different fields were researched and compared to evaluate 4D scanning as the most suitable method for capturing tissue deformability in vivo. In particular, it should be considered that the human body has different deformation capabilities depending on age, the amount of muscle and body fat. In addition, different tissue zones have different mechanical properties, so it is essential to identify and classify them to back up these properties for the simulation. It has been shown that by digitising the obtained data of the different defined applied pressure levels, a prediction of the deformation of the tissue of the exact person becomes possible. As technology advances and data sets grow, this approach has the potential to reshape how we verify fit digitally with soft avatars and leverage their realistic soft tissue properties for various practical purposes.
Today many vertical retailers are operating different sales channels at the same time and are respon-sible for the range of products in all sales channels. The purpose of this paper is to examine whether for vertical fashion retailers a format-specific assortment policy can be observed on the German mar-ket. To investigate this topic in addition to secondary data of a literature research, quantitative prima-ry data was collected through a structured observation by conducting store checks. The combination provides insights into the research topic, allows to build hypotheses and to get a current and specific answer on the research topic. The study revealed all vertical retailers exploit the advantage of unlim-ited capacity of the online shop by offering in this channel mainly the broadest and deepest assort-ment. Within the retail store the vertical retailers focus on offering full-price goods for the current season in full size sets. Compared to the online shop here are less styles sophisticated presented and adjusted on the sales floor. For the outlet channel all brands showed a higher density of products and at least a price reduction of 30 per cent. The present paper is limited by time, depth and language of secondary data collection. As the study only conducted quantitative data within limited observations additional visual data over a longer period is necessary.
Purpose of the research paper is to illuminate the subject of assortment policy in the German fashion e‐commerce market. A short literature review is conducted in order to set up a system of characteristics to contemplate assortments on a strategic level. In a second step, structured observations are conducted to quantitatively analyze and compare the assortments of the leading online fashion retailers within Germany. Based on literature, the following characteristics for a classification of assortments can be identified: assortment structure, assortment size, assortment width, assortment depth, assortment consistency and rotation, price level, quality mix, fashion degree as well as the mix of private labels and manufacturer brands. Furthermore, the results of the empirical analysis show that there are currently five leaders within the nalyzed market: Amazon, Otto, Zalando, Baur and About You. Among these five market leaders, Amazon positions itself as a retailer that not only offers an enormous assortment size, but also the lowest entry prices as well as the broadest price dispersion. Through the development of the system of characteristics for assortment analysis and the examination of the current market environment, the findings of this paper contribute to the current state of the art in both theoretical and practical aspects.
Kreativität, Problemlösekompetenz und kollaboratives Arbeiten werden in zahlreichen internationalen Studien sowie von der OECD (2017) als Schlüsselkompetenzen des 21. Jahrhunderts definiert. Ungeachtet dessen orientieren sich viele Lehr-Lern Methoden noch immer an der Vermittlung vordefinierter Lösungswege. Studien im Sekundarbereich in den USA, Deutschland und Asien zeigen, dass Design Thinking durch seine kreativen und kollaborativen Elemente zu einem nachhaltigeren Lernerfolg bei Lernenden und seitens der Lehrenden zu höherer Zufriedenheit bei der Vermittlung der Inhalte führen kann.
Kernelemente des Design Thinking sind: der iterative Prozess mit seinen Phasen Verstehen, Beobachten, Sichtweisen definieren, Ideen finden, Prototypen bauen, Testen; die Arbeit in multidisziplinären Teams sowie die Nutzerorientierung bei der Definition der Aufgabe (Brown, 2009). Die Phasen des iterativen Prozesses weisen eine hohe Kongruenz mit den prozessorientierten Kompetenzen des Faches Kunst/Werken und des Sachunterrichts gemäß dem Bildungsplan für Grundschulen (Ministerium für Kultus, Jugend und Sport Baden Württemberg, 2016) auf. Im Rahmen eines interdisziplinären Promotionsvorhabens an der PH Freiburg soll, basierend auf einem qualitativen Forschungsdesign, untersucht werden, inwieweit sich Design Thinking eignet, Kreativität, Problemlösekompetenz und kollaboratives Arbeiten von Grundschulkindern in Kunst/Werken und im Sachunterricht aus Sicht von Lehrpersonen zu fördern. Vorstudien mit Lehrpersonen und Ausbildungslehrkräften, bei welchen Erhebungen per Fragebogen nach Teilnahme an einem Design Thinking Workshop eingesetzt wurden, sowie zwei Pilotunterrichtseinheiten an Grundschulen mit Teilnehmender Beobachtung, Experteninterviews und Kinderinterviews in Kleingruppen, zeigen erste Ergebnisse.