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A MATLAB toolbox was developed both for teachers performing quick experimental demonstrations during lectures and for students practicing measurement and frequency analysis procedures. The conceptual purpose was to support fundamental acoustics courses with contents defined by the DEGA recommendation 102. All implemented functions and parameters are visible at once and quickly adjustable by a GUI without submenus. A user manual is provided with explanations of how to get started and how all implemented functions can be applied. The toolbox probably still contains bugs. All users are welcome to inform the author about their experiences and proposals for improvement. In future it is planned to convert "Acoustics" to the MATLAB app designer format as Mathworks announced GUIDE to be replaced. Useful extensions would be additional tabs containing animations of sound propagation phenomena or sound fields caused by different sources.
Type 1 diabetes is a chronic and a life threatening disease: an adjusted treatment and a proper management of the disease are crucial to prevent or delay the complications of diabetes. Although during the last decade the development of the artificial pancreas has presented great advances in diabetes care, the multiple daily injections therapy still represents the most widely used treatment option for type 1 diabetes. This work presents the proposal and first development stages of an application focused on guiding patients using the continuous glucose monitors and smart pens together with insulin and carbohydrates recommendations. Our proposal aims to develop a platform to integrate a series of innovative machine learning models and tools rigorously tested together with the use of the latest IoT devices to manage type 1 diabetes. The resulting system actually closes the loop, like the artificial pancreas, but in an intermittent way.
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.
There are several intra-operative use cases which require the surgeon to interact with medical devices. I used the Leap Motion Controller as input device for three use-cases: 2D-interaction (e.g. advancing EPR data), selection of a value (e.g. room illumination brightness) and an application point and click scenario. I evaluated the Palm Mouse as the most suitable gesture solution to coordinate the mouse and advise to use the implementation using all fingers to perform a click. This small case study introduces the implementations and methods that result those recommendations.
Today many scientific works are using deep learning algorithms and time series, which can detect physiological events of interest. In sleep medicine, this is particularly relevant in detecting sleep apnea, specifically in detecting obstructive sleep apnea events. Deep learning algorithms with different architectures are used to achieve decent results in accuracy, sensitivity, etc. Although there are models that can reliably determine apnea and hypopnea events, another essential aspect to consider is the explainability of these models, i.e., why a model makes a particular decision. Another critical factor is how these deep learning models determine how severe obstructive sleep apnea is in patients based on the apnea-hypopnea index (AHI). Deep learning models trained by two approaches for AHI determination are exposed in this work. Approaches vary depending on the data format the models are fed: full-time series and window-based time series.
The aim of this paper is to show to what extent Artificial Intelligence can be used to optimize forecasting capability in procurement as well as to compare AI with traditional statistic methods. At the same time this article presents the status quo of the research project ANIMATE. The project applies Artificial Intelligence to forecast customer orders in medium-sized companies.
Precise forecasts are essential for companies. For planning, decision making and controlling. Forecasts are applied, e.g. in the areas of supply chain, production or purchasing. Medium-sized companies have major challenges in using suitable methods to improve their forecasting ability.
Companies often use proven methods such as classical statistics as the ARIMA algorithm. However, simple statistics often fail while applied for complex non-linear predictions.
Initial results show that even a simple MLP ANN produces better results than traditional statistic methods. Furthermore, a baseline (Implicit Sales Expectation) of the company was used to compare the performance. This comparison also shows that the proposed AI method is superior.
Until the developed method becomes part of corporate practice, it must be further optimized. The model has difficulties with strong declines, for example due to holidays. The authors are certain that the model can be further improved. For example, through more advanced methods, such as a FilterNet, but also through more data, such as external data on holiday periods.
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.
It has not yet been possible to achieve the desired aim of decoupling economic growth from global material demand. Small and medium sized enterprises (SMEs) represent the backbone of most industrialized economies. Although material efficiency is of vital importance for many SMEs, few of them actually treat it as their top priority. There is a cornucopia of tools and methods available which can be used for material efficiency purposes. These, however, have gained little ground in the SME-field. This work deals with the enabling factors for material efficiency improvements in manufacturing SMEs and projections towards aspects of supply chain and circular economy. A multi-disciplinary decoupling approach for manufacturing SMEs and an implementation roadmap for further practical development are proposed. The approach combines appropriate complexity of technology and socio-economic considerations. It enables a connection of existing methods and the implementation of established information technologies.
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.
This case study of Breuninger aims to analyze how Breuninger adapts to the emerging omnichannel environment in fashion business. From a consumer’s perspective Breuninger and the general omnichannel strategy of Breuninger is explained, before the loyalty program of Breuninger is analyzed in detail. Key factors as the mobile app and the mobile Breuninger card, social media, direct mail and in-store capabilities are described. A discussion chapter finalizes the case.
In a globalized world the importance of a proper segmentation method for identifying target consumers has been increasing. Vast majority of the research in this area focuses on the usage or development of different techniques. Lifestyle is a good criterion for dividing people into groups which then can be better targeted. This article addresses the research question, which classical methods exist to segment markets with the aid of lifestyle. The purpose of this paper is to illustrate several instruments, such as A.I.O., Roper Consumer Styles, VALS-Method, the Sinus-Milieus, Sigma-Milieus, RISC-Method and Semiometrie but also Discriminant and Conjoint Analysis which proved of value in the past. Furthermore it deals with the benefits of this methods but weaknesses are also considered. Therefore several existing literature is examined, and information is collected by institutes providing the typologies. Obvious is, that new methods e.g. predictive analytics already play a major role in marketing, because it can be found much literature about it. In the literature research also appear research implications, because besides the provided information from institutes and journals, there is hardly no data to find if and how companies use the instruments. Furthermore, some important databases cannot be scanned because they are not accessible without paying.
The potentials and opportunities created by digitized healthcare can be further customized through smart data processing and analysis using accurate patient information. This development and the associated new treatment concepts basing on digital smart sensors can lead to an increase in motivation by applying gamification approaches. This effect can also be used in the field of medical treatment, e.g. with the help of a digital spirometer combined with an app. In one of our exemplary applications, we show how to control an airplane within an app by breathing respectively inhaling and exhaling. Using this biofeedback within a game allows us to increase the motivation and fun for children that need to perform necessary exercises.
Detecting semantic similarities between sentences is still a challenge today due to the ambiguity of natural languages. In this work, we propose a simple approach to identifying semantically similar questions by combining the strengths of word embeddings and Convolutional Neural Networks (CNNs). In addition, we demonstrate how the cosine similarity metric can be used to effectively compare feature vectors. Our network is trained on the Quora dataset, which contains over 400k question pairs. We experiment with different embedding approaches such as Word2Vec, Fasttext, and Doc2Vec and investigate the effects these approaches have on model performance. Our model achieves competitive results on the Quora dataset and complements the well-established evidence that CNNs can be utilized for paraphrase recognition tasks.
Purpose of this research paper is to assess the state of the art concerning the relevance of consumer segmentation models in the fashion industry with regards to current changes in technology, market structure and consumer behavior.
The paper is composed of a qualitative literature review and an empirical study in form of a survey. They are contrasted in order to identify both similarities and differences.
Findings reveal that consumer segmentation is still relevant. Notwithstanding, an adaptation of classification models is necessary according to occurring changes. External models, segmenting consumers by means of lifestyle or fashion typologies, are used. However, it is striking that most companies of the empirical study already apply internal segmentation models with tendency to rise. Moreover, research has shown that consumer classification models in the USA make use of different criteria than in Europe.
Language barriers within the literature review and a low sample size in the empirical study give research limitations. Future management implications can be directed to the identification of procedures for the efficient application of internal segmentation models.
This paper investigates the possibility to effectively monitor and control the respiratory action using a very simple and non invasive technique based on a single lightweight reduced-size wireless surface electromyography (sEMG) sensor placed below the sternum. The captured sEMG signal, due to the critical sensor position, is characterized by a low energy level and it is affected by motion artifacts and cardiac noise. In this work we present a preliminary study performed on adults for assessing the correlation of the spirometry signal and the sEMG signal after the removal of the superimposed heart signal. This study and the related findings could be useful in respiratory monitoring of preterm infants.
Curriculum design for the German language class in the double-degree programme business engineering
(2017)
This paper aims to give an overview on how German is taught as a foreign language to students enrolled in the Bachelor of Business Engineering, a double-degree programme offered in Universiti Malaysia Pahang. The double degree students have the opportunity to complete their first two years of study in Malaysia and their last two years in Germany. Taking the TestDaF examination is compulsory for double-degree students. Hence, the German Language curriculum has been meticulously planned to ensure the students would be competent in the language. As such, the settings of the language class are discussed thoroughly in this paper. Additionally, it also discusses the challenges faced in teaching German as foreign language. This paper ends with some suggestions for improvement.
Loyalty programs become more important in an omnichannel environment of fashion retail business. After the definition of customer loyalty and loyalty programs the main characteristics of omnichannel loyalty programs are described. As touchpoints of omnichannel loyalty programs mobile, social media, direct mail and in-store capabilities are detailed. A discussion chapter closes with recommendations for fashion retailers.
Sleep is essential to existence, much like air, water, and food, as we spend nearly one-third of our time sleeping. Poor sleep quality or disturbed sleep causes daytime solemnity, which worsens daytime activities' mental and physical qualities and raises the risk of accidents. With advancements in sensor and communication technology, sleep monitoring is moving out of specialized clinics and into our everyday homes. It is possible to extract data from traditional overnight polysomnographic recordings using more basic tools and straightforward techniques. Ballistocardiogram is an unobtrusive, non-invasive, simple, and low-cost technique for measuring cardiorespiratory parameters. In this work, we present a sensor board interface to facilitate the communication between force sensitive resistor sensor and an embedded system to provide a high-performing prototype with an efficient signal-to-noise ratio. We have utilized a multi-physical-layer approach to locate each layer on top of another, yet supporting a low-cost, compact design with easy deployment under the bed frame.
Determination of accelerometer sensor position for respiration rate detection: initial research
(2022)
Continuous monitoring of a patient's vital signs is essential in many chronic illnesses. The respiratory rate (RR) is one of the vital signs indicating breathing diseases. This article proposes the initial investigation for determining the accelerometric sensor position of a non-invasive and unobtrusive respiratory rate monitoring system. This research aims to determine the sensor position in relation to the patient, which can provide the most accurate values of the mentioned physiological parameter. In order to achieve the result, the particular system setup, including a mechanical sensor holder construction was used. The breathing signals from 5 participants were analyzed corresponding to the relaxed state. The main criterion for selecting a suitable sensor position was each patient's average acceleration amplitude excursion, which corresponds to the respiratory signal. As a result, we provided one more defined important parameter for the considered system, which was not determined before.
The field of breath analysis has developed to be of growing interest in medical diagnosis and patient monitoring. The main advantages are that it’s noninvasive, painless and repeatable in flexible cycles. Even though breath analysis is being researched for a couple of decades there are still many unanswered questions. Human breath contains volatile organic compounds which are emitted from inside the body. Some of these compounds can be assigned to specific sources, such as inflammation or cancer, but also to non health related origins. This paper gives an overview of breath analysis for the purpose of disease diagnosis and health monitoring. Therefore, literature regarding breath analysis in the medical field has been analyzed, from its early stages to the present. As a result, this paper gives an outline of the topic of breath analysis.
Information and communication technologies support telemedicine to lower health access barriers and to provide better health care. While the potential in Active Assisted Living (AAL) is increasing, it is difficult to evaluate its benefits for the user, and it requires coordinated actions to launch it. The European Commission’s action plan 2012–2020 provides a roadmap to patient empowerment and healthcare, to link up devices and technologies, and to invest in research towards the personalized medicine of the future. As a quickly developing area in medicine, telemonitoring is a demanding field in research and development. Telemonitoring is an essential component of personalized medicine, where health providers can obtain precise information on outcare or chronic patients to improve diagnosis and therapy and also help healthy persons with prevention support. Telemonitoring combines mobile and wearable devices with the personal AAL home environment, a private or (partly) supervised home, most often called ’smart home’. The focus of this workshop is on new hardware and software solutions specifically designed to be applicable in AAL environments to empower patients. This workshop presents system-oriented solutions covering wearable and AAL-embedded devices, computer science infrastructure both at the users’ and the medical premises, to handle the data and decision support systems to support diagnose and treatment.
The purpose of this paper is to examine the effects of perceived stress on traffic and road safety. One of the leading causes of stress among drivers is the feeling of having a lack of control during the driving process. Stress can result in more traffic accidents, an increase in driver errors, and an increase in traffic violations. To study this phenomenon, the Stress Perceived Questionnaire (PSQ) was used to evaluate the perceived stress while driving in a simulation. The study was conducted with participants from Germany, and they were grouped into different categories based on their emotional stability. Each participant was monitored using wearable devices that measured their instantaneous heart rate (HR). The preference for wearable devices was due to their non-intrusive and portable nature. The results of this study provide an overview of how stress can affect traffic and road safety, which can be used for future research or to implement strategies to reduce road accidents and promote traffic safety.
The importance of sleep for human life is enormous. It affects physical, mental, and psychological health. Therefore, it is vital to recognise sleep disorders in a timely manner in order to be able to initiate therapy. There are two methods for measuring sleep-related parameters - objective and subjective. Whether the substitution of a subjective method for an objective one is possible is investigated in this paper. Such replacement may bring several advantages, including increased comfort for the user. To answer this research question, a study was conducted in which 75 overnight recordings were evaluated. The primary purpose of this study was to compare both ways of measurement for total sleep time and sleep efficiency, which are essential parameters for, e.g., insomnia diagnosis and treatment. The evaluation results demonstrated that, on average, there are 32 minutes of difference between the two measurement methods when total sleep time is analysed. In contrast, on average, both measurement methods differ by 7.5% for sleep efficiency measurement. It should also be noted that people typically overestimate total sleep time and efficiency with the subjective method, where the perceived values are measured.
When wearing compressive garments, the tissue of the human body is altered in relation to its natural shape by the properties of the applied material and by the pattern construction used.
To check the fit of garments, both construction and selected materials can be virtually simulated in 3D on avatars in corresponding CAD programs before fabrication.
The software Blender allows the modelling of an avatar and to generate in respective to the different tissue zones with their specific properties to adjust them with soft body physics according to the testing of real soft tissue but the models in Blender are mainly using linear springs.
After definition and the history of podcasts, in this book the role of podcasts in the communication strategy is mapped out. Podcast production, podcast types, podcast structures, and podcast advertising are explained. Podcast audiences and podcast in the fashion industry are introduced.
In a thorough explorative analysis, a general exploration of the podcast offering of the fashion sector was conducted. Then a selected podcast analysis with evaluation and conclusion, including a discussion of the future use of podcasts closes this book.
Purpose: The purpose of this paper is to describe and discuss the current state of fashion business academic education worldwide. This is motivated by the wish to develop recommendations for the fashion business bachelor program of Reutlingen Uni versity.
Design/methodology/approach: This paper is based on a systematic review of relevant fashion business academic programs. A qualitative comparison is conducted through a categorization of the programs’ content and a score system evaluating the programs’ concepts.
Findings: Key findings were that several factors ensure successful fashion business education: Industry connections, international networks, project-based work, personalized career services and innovative approaches in teaching that include all steps along the fashion value chain.
Research limitations/implications: The research was primarily limited due to the limited number of schools assessed. As a result of the restricted time frame, those schools that were presented could only be analyzed regarding a few aspects. Future research should focus on a more in-depth analysis and further-reaching comparisons, e.g. comparisons with teaching concepts outside the fashion business area or with requirements by fashion companies.
Knowing your customer, i.e. your target market, is critical for the success of a company and its’ products. The current socio-demographic changes in the United States issue new challenges to marketers and practitioners. Actual fashion consumer seg-mentation approaches within the United States have received little attention in media and scholarly literature. Therefore, the aim of this paper is to present the existing academic literature addressing fashion consumer style preferences, particularly highlighting the most promising consumer groups within the United States: Hispanics and African-Americans. For this, a literature review was chosen with a subsequent critical discussion and comparison of both segments including findings of academic researches as well as market research agencies and actual lifestyle clustering approaches regarding these consumer groups. The findings show, whilst the published literature on consumer segmentation in the apparel industry provides only a surficial understanding of the fashion buying behaviors of Hispanics and Black Americans, it could be found that both ethnic groups are highly interested in fashion, price sensitive, and they are over indexed in apparel spending habits. Especially within the Hispanic population factors such as age and level of acculturation play a vital role in the purchasing choice of apparel, footwear and accessories and require further research.
Generating synthetic data is a relevant point in the machine learning community. As accessible data is limited, the generation of synthetic data is a significant point in protecting patients' privacy and having more possibilities to train a model for classification or other machine learning tasks. In this work, some generative adversarial networks (GAN) variants are discussed, and an overview is given of how generative adversarial networks can be used for data generation in different fields. In addition, some common problems of the GANs and possibilities to avoid them are shown. Different evaluation methods of the generated data are also described.
This workshop addressed scientific research and development to acquire physiological signals, process signals, and extract relevant data for further analysis. There are very different domains of application, for example. Tiredness and drowsiness are responsible for a significant percentage of road accidents. There are different approaches to monitoring driver drowsiness, ranging from the driver’s steering behavior to in-depth analysis of the driver, e.g., eye tracking, blinking, yawning, or Electrocardiogram (ECG). One of the leading causes of road accidents in Egypt is trucks, buses, cars, motorcycles, and pedestrians, all sharing the same infrastructure. The result is that there are more than 12,000 fatalities in road accidents every year. Thousands are injured, and some suffer long-term disabilities. A similar effect can be observed in Germany for all types of vehicles. According to the Federal Statistical Office, a high percentage of accidents involving personal injury are directly or indirectly caused by drowsiness.
A different application domain is sleep monitoring: Healthy and sound sleep is a prerequisite for a rested mind and body. Both form the basis for physical and mental health. Healthy sleep is counteracted by sleep disorders, the medically diagnosed frequency of which increases sharply from the age of 40. Increasing acceptance can be promoted by monitoring vital signs during sleep over long periods through the exclusive use of noninvasive technologies. In the case of objective measurement, the vital signs are measured to calculate the sleep phases or sleep efficiency and, after applying the appropriate algorithms, to record the sleep quality. About a quarter of all Germans have the feeling of sleeping poorly. The disruptive factors include problems falling asleep or the subjective feeling that sleep is not restful. About half of those subjectively affected have consulted a doctor. Older people and people living alone are particularly affected. There is no doubt that sleep abnormalities can lead to poor performance throughout the day, physical/somatic illnesses, psychological problems, or even premature death. Prevention, early detection, and therapy support are relevant factors impacting the personal quality of life.
The presented approaches have different application domains but share standard methodologies and technologies. Cross-domain thinking and application are essential to successful data acquisition and processing, either with traditional or cutting-edge approaches.
Since 2000, Indian special economic zones were established with the intention to attract foreign direct investment. We present a first empirical assessment with new data from 1980 to 2010 and evaluate the outcome after 10 years. In general, our empirical results confirm that special economic zones attract FDI statistical significantly. Another finding of the study is that open economies with stable inflation attract more FDI than small and closed economies.
This research is about Omnichannel Retailing and addresses the question how the omnichanneling of retailers in the fashion market can be measured. Our sources will include books, interviews, newspapers and scientific databases.
Omnichanneling is a current topic in the fashion market, retailers all over the world face the question on how to adapt to the challenges Omnichannel Retailing sets. We are going to define what Omnichanneling is by explaining the differences between Multiple-, Multi-, Cross- and Omnichannel Retailing. After we defined omnichanneling itself, we took a set of 26 retailers to evaluate regarding their Omnichannel capabilities. Then we create an index with criteria that can measure the Omnichannel capability of each retailer.
The Omnichannel Score is based on 31 criteria, which analyze the retailers in offline, online, mobile and social aspects enables to see differences between retailers. Our findings were that retailers in the US fashion market are more advanced in Omnichannel Retailing than retailers in the German fashion market. Our top three Omnichannel retailers were Sears with an Omnichannel Score of 91, followed by KOHL’S and Marks&Spencer, both with a Omnichannel Score of 88. The best Omnichannel Retailer from Germany was Adidas with the fourth place and an Omnichannel Score of 81.
India’s growth: perspectives for Indo-European business “Skilled labour in India: bridging the gap”
(2011)
The following paper is based on a survey conducted for ESB Business School and will show how German companies perceive India’s labour market. Besides existing geographical and sectoral gaps we will reveal gaps in the required qualification profile. Thinking merely of hard qualification factors like education levels, skills etc., though, would be short-sighted. Often cited intercultural qualifications also play an important role.
What can be done? What should be done to bridge these gaps? These will be the leading questions of this chapter. We will discuss some solutions – not forgetting that the problems German companies face are complex and knowing there is no ideal way. However, we will see that some of the most urgent problems can be solved or reduced by Indo-European or Indo-German co operation models in the field of vocational training and institutions of higher education.
Integrating tools and applications into a clinically useful system for individual continuous health data surveillance requires an architecture considering all relevant medical and technical conditions. Therefore, the requirements of an integrated system including a health app to collect and monitor sensor data to support personalized medicine are analyzed. The structure and behavior of the system are defined regarding the specific health use cases and scenarios. A vendor-independent architecture, which enables the collection of vital data from arbitrary wearables using a smartphone, is presented. The data is centrally managed and processed by attending physicians. The modular architecture allows the system to extend to new scenarios, data formats, etc. A prototypical implementation of the system shows the feasibility of the approach.
Purpose: The purpose of this study was to investigate the value of the web representation of certain fashion hot spots and how these results can be shown on fashion maps in an illustrated way.
Design/methodology/approach: A new ranking was created, which was evaluated with a self-instructed index, to gain solid results. Numbers were collected from Google, Instagram, Facebook, Twitter and web.alert.io. Additionally, fashion maps were created for an illustrative visualization of the results.
Findings: Compared with the ranking of a trend forecasting agency, called Global Language Monitor, which concepted a ranking of non-virtual fashion cities, the web representation and therefore the ranking of the research project, differs mainly in the situation of the cities among the first 10, viz. the rank on which a city occurs, but fewer in the actual cities mentioned.
Research limitations: The research was limited to subjective analysis of data, leading to partly subjective results, as well as the selected number of social media platforms, that had been used.
Originality/value: This is the first study to explore the web representation value of fashion metropolises in comparison to their non-virtual ranking. The results are partly based on results that already existed, concerning transformations of fashion cities or in general which cities own the status of a fashion city.
This is the first copy of JIEBS. The papers it presents are the result of a call for papers CEBS made in 2011. We actually received far more interesting papers and research reports than expected.They all passed a double blind review and the papers naturally are the original work of the named authors. The choice we finally made was also influenced by the topic of the CEBS annual conference 2011, namely the influence of infrastructure and skilled labour on Indo-European Business. The papers analyse structure and explain many issues related to this, they raise questions and point towards areas for further research and they form the nucleus of this new and currently only scientific platform for Indo-European business studies.
This case study describes the emerging customized omnichannel loyalty solution of Marc O’Polo from a customer’s perspective. After the introduction of Marc O’Polo and their general omnichannel strategy, the loyalty program is described in detail, like Marc O’Polo for members and the mobile app, social media, direct mail and in-store capabilities. A discussion chapter closes the case study with research implications and open questions for Marc O’Polo.
In recent years Indonesia has been confronted with an excessive generation of municipal solid waste (MSW), predominantly present in the form of organic refuse. While moving towards integrated solid waste management (ISWM) is an important strategy used to control its generation, it is also now recognized that economic approaches need to be promoted as well in order to tackle the problem concertedly. In this case study, empirical approaches are developed to understand how market instruments could be introduced into environmental services and how to apply co-benefit approach in a green economy paradigm for Indonesia. We investigate the feasibility of introducing market instruments in Indonesia by appliying local co-benefit initiatives adapted from German experiences in integrating market instruments into MSW management practices. Currently co-benefit activities are undertaken in the Sukunan village (Yogjakarta) to promote waste composting using market incentives in the framework of community-based solid waste management (CBSWM). This scheme aims at reducing MSW generation at its source and mobilizing people to be involved in waste separation (organic and non-organic) at household levels. As a result, about 200,000 t of CO2 emissions could be successfully reduced annually. By integrating market instruments into waste management practices, the result of our studies sugggests that Indonesia could make positive changes to its environmental policy and regulation of MSW at local levels. The country's policymakers have played important roles in promoting the effectiveness of urban development with co-benefits approaches to facilitate its transition towards a green eccnomy.
Sleep analysis using a Polysomnography system is difficult and expensive. That is why we suggest a non-invasive and unobtrusive measurement. Very few people want the cables or devices attached to their bodies during sleep. The proposed approach is to implement a monitoring system, so the subject is not bothered. As a result, the idea is a non-invasive monitoring system based on detecting pressure distribution. This system should be able to measure the pressure differences that occur during a single heartbeat and during breathing through the mattress. The system consists of two blocks signal acquisition and signal processing. This whole technology should be economical to be affordable enough for every user. As a result, preprocessed data is obtained for further detailed analysis using different filters for heartbeat and respiration detection. In the initial stage of filtration, Butterworth filters are used.
There is no doubt that the amplification of channel integration towards an omni-channel structure is a powerful idea whose time has finally come. The digitally cross-linked world postulates all-encompassing, ubiquitous, and unobtrusive future services. In the concomitant, increasingly competitive market, retailers are starting to lay the foundation for omnichannel, meeting the expectations of a digitally cunning audience wanting their shopping experience to be as seamless and uncomplicated as possible. Nevertheless, recent researches show that there are still enough avenues for further research on omnichannel. Until now, the performance of companies was solely considered by experts from a suppliers’ point of view. It would be rather interesting to find out whether the desire to meet the increased cus-tomer expectations is also recognized by the customers themselves. This paper seeks to answering how the purchasing behavior has changed and what customers demand. In addition, it elaborates the opportunities that are promoted by omni-channel. Searching out all the effects, the paper will get to a final step, where it can be attested how the omnichannel performance of fashion and lifestyle retailers can be measured from a consumers’ perspective by developing an exclusive index. The study is confined to four fashion and lifestyle retailers: Hugo Boss AG, Levi Strauss & Co, Pull and Bear as well as COS. Using the scientific method of mystery shopping and a multi-item checklist including 54 key performance indicators, the paper aims to examine to which extend the four selected retailers provide a seamless customer journey, according to the five decision-making phases.
In summary, we believe that current “sleep monitoring” consumer devices on the market must undergo a more robust validation process before being made available and distributed in the general public. This is especially noteworthy as there have been first reports in the literature that inaccurate feedback of such consumer devices can worry subjects and may even lead to compromised well-being of the user.
A clinically useful system for individual continuous health data monitoring needs an architecture that takes into account all relevant medical and technical conditions. The requirements for a health app to support such a system are collected, and a vendor independent architecture is designed that allows the collection of vital data from arbitrary wearables using a smartphone. A prototypical implementation for the main scenario shows the feasibility of the approach.
Assistive environments are entering our homes faster than ever. However, there are still various barriers to be broken. One of the crucial points is a personalization of offered services and integration of assistive technologies in common objects and therefore in a regular daily routine. Recognition of sleep patterns for the preliminary sleep study is one of the Health services that could be performed in an undisturbing way. This article proposes the hardware system for the measurement of bio-vital signals necessary for initial sleep study in a nonobtrusive way. The first results confirm the potential of measurement of breathing and movement signals with the proposed system.
In times of e-commerce and digitalization, new markets are opening, young companies have the possibility to grow and new perspectives arise in terms of customer relationship. Customers require more possibilities of personalization. In the same time, companies have access to new and especially more information about the customer. Seems like it was a correlation that could evolve greatly if there weren't privacy issues. Vast amount of data about consumers are collected in Big Data warehouses. These shall be analyzed via predictive analytics and customers shall be classified by algorithms like clustering models, propensity models or collaborative filtering. All these subjects are growing in importance, as they are shaping the global marketing landscape. Marketers develop together with IT scientists new ways of analyzing customer databases and benefit from more accurate segmentation methods as that have been used until now. The following paper shall provide a literature review on new methods of consumer segmentation regarding the high inflow of new information via e-commerce. It will introduce readers in the subject of predictive analytics and will discuss several predictive models. The writing of the paper is not based on own empirical researches, but shall serve as a reference text for further researches. A conclusion will complete the paper.
Semi-automated image data labelling using AprilTags as a pre-processing step for machine learning
(2019)
Data labelling is a pre-processing step to prepare data for machine learning. There are many ways to collect and prepare this data, but these are usually associated with a greater effort. This paper presents an approach to semi-automated image data labelling using AprilTags. The AprilTags attached to the object, which contain a unique ID, make it possible to link the object surfaces to a particular class. This approach will be implemented and used to label data of a stackable box.
The data is evaluated by training a You Only Look Once (YOLO) net, with a subsequent evaluation of the detection results. These results show that the semi-automatically collected and labelled data can certainly be used for machine learning. However, if concise features of an object surface are covered by the AprilTag, there is a risk that the concerned class will not be recognized. It can be assumed that the labelled data can not only be used for YOLO, but also for other machine learning approaches.