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Due to the rising need for palliative care in Russia, it is crucial to provide timely and high-quality solutions for patients, relatives, and caregivers. A methodology for remote monitoring of patients in need of palliative care and the requirements will be developed for a hardware-software complex for remote monitoring of patients' health at home.
During two researches the influence of technologies on sleep were analyzed. The first one is about the effect of light on the circadian rhythm and as consequence on sleep quality of persons in a vegetative state. The second one, which is still running, surveys the influence of several technical tools on the sleep of elderly people living in a nursing home.
This paper summarises the experiences with sustainability reporting in a very wide meaning at Universities of Applied Sciences (UoAS). It focuses on the communication of sustainability aspects and activities of universities. It provides a recommendation, a model for communicating the sustainability activities of universities and emphasises the values of this appraoch. This paper aims to find the most effective ways to convey education for sustainable development to a broad public and initiate communication about sustainability aspects with society.
The paper is based on action research done at two universities about the ways in which academic institutions can communicate with their stakeholders in order to report about their own role as a responsible university and also to make an impact on the sustainable development on a local and global scale.
Research is focussed on experiences at Universitites of Applied Sciences with their strong focus on applied research, education and transfer. However, these results can be helpful for each academic institution that wants to make a positive impact on society. The concept which we present focusses on the possible impact which universities can generate.
Seen as the contribution to the research field of sustainabitliy reporting the paper points out that a continuous qualitative reporting process with a focus on education for SD is an adequate and efficient approach to sustainability reporting for universities and an effective way to reach a broad public.
We show that there are several efficient methodss of communication ranging from the traditional sustainability report to publications which address the public and to more innovative methods using the web 2.0. We show and argue that for universities, alternative ways of sustainability communication may be more effective to achieve the sustainability mission.
The concept which we present gives the universities a broader impact on society and helps them to support sustainable development in an efficient way.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.