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This master thesis aims to investigate the current state of wastewater treatment practices in the Jordanian cement industry and explore the potential for transferring advanced techniques from the global state of the art. The research will analyze the existing wastewater management approaches, identify areas for improvement, and provide recommendations for implementing more efficient and environmentally sustainable treatment methods in selected Jordanian cement companies. By examining the current challenges and opportunities, this study seeks to contribute to the advancement of wastewater treatment in the Jordanian cement sector, ultimately promoting environmental stewardship and responsible industrial practices.
Buildings are as diverse as people themselves. As a result, it has become difficult to keep track of the technologically possible measures. But climate change is advancing and those who do not adapt to this change will have a hard time in the future. The goal is to investigate Green Buildings and identify possibilities for KSB to adapt to the future.
The research topic is as follows: "The Future of Sustainable Building: Potential Analysis of Green Buildings from a Water Management Perspective exemplified by KSB SE & Co. KGaA." The research topic was approached in two ways. Firstly, a literature search was carried out on existing green buildings. Secondly, KSB internal and KSB external experts were interviewed to assess the future situation. In this way, potentials for KSB in the area of green building were identified. The potentials were subsequently evaluated using the Priority Model of Sustainability. For this purpose, beneficial attributes were named for the respective dimension of sustainability and the respective potential. The attributes are used for potential analysis and were all worth one point in each dimension. The point scale starts at 0 (if a potential in a particular dimension does not offer any namable advantages) and ends at a maximum score of 10.
The results suggest that increased digitalization of the company's own products will bring great opportunities in the future. In addition, the results and research show that in the future the focus will be much more on the natural handling of rainwater. Similar to the increase in interest in rainwater management, there are opportunities for OEM partnership with urban greening companies.
Continued engagement in these matters will be the way forward.
Maintaining balance in the hydrological cycle is crucial for nature, but extreme weather events such as droughts and heavy downpours can disrupt it. Unfortunately, the frequency of such events has increased in recent years and is expected to continue in the future (IPCC, 2021). Urban areas are particularly vulnerable to this condition, due to its sealed surfaces and limited green spaces resulting from anthropogenic activities. Decentralized stormwater management strategies are realised to be better in mitigating the effects of such events, and this research aims to explore the importance of green buildings in managing stormwater in the selected catchment areas. Two properties have been chosen for the study: an elementary school in Schauenstein and Hof University of Applied Science. The study examines in detail the general characteristics of the chosen areas, their historical climatic data, and the KOSTRA DATA (refer 3.7). The research analyses the selected buildings and their surrounding properties, the various components of their water balance involved, the methods to calculate them, its advantages, limitations, and requirements were also compared. Based on the study, an excel-based calculation model has been developed focusing on the stormwater management aspect, to find out the major components involved in the water balance of the green building and its surrounding properties that can control surface runoff from the property. The developed calculation model works on the major aspects of water accumulation and consumption of selected green buildings and its surroundings. The tool can be used to predict runoff from the properties during different storm events, based on which the volume of a stormwater collection tank can be calculated, which can store runoff from the catchment area and can be used during droughts for irrigation purposes, thereby reducing the pressure on drainage flow and water treatment plants. The study also tries to identify the effects of water balance parameters like rainfall, evapotranspiration and storage on runoff from a property. The model also checks the tank's condition for future storm events with a 3, 5,10 and 100-year return period, using KOSTRA DATA 2020. Both the study areas are assumed to have green roofs, and the runoff results from the roofs occupied by them are validated using detention modeller software developed by green roof diagnostics.
Approximately 71% of Earth's surface is covered by water, with only 3% being fresh water suitable for human use, a majority of which is trapped in glaciers and permafrost. Freshwater ecosystems, vital for sustaining life and biodiversity, face heavy utilization by humans, mainly for agriculture, industry, and municipal needs, leading to an annual freshwater consumption of 32,928 km³. Agriculture is responsible for approximately 70% of this consumption, highlighting the critical need to enhance water-use efficiency in the face of escalating scarcity and the projected requirement for a 15% increase in freshwater withdrawals, necessary to support a 50% growth in agricultural production by 2050. Soil health plays a pivotal role in sustainable agriculture, influencing plant production, water quality, and nutrient recycling. In this context, precision agriculture, particularly sensor-based approaches like LoRaWAN, emerges as a key solution with its low power usage, long-range capabilities, and cost-effectiveness. However, their adoption is limited in small to medium-scale farms, primarily in regions lacking mechanized farming, due to high initial investments and extended return periods. Challenges include the cost of new technology adoption, training, and the high expense of purchasing and maintaining advanced hardware.
This thesis focuses on making precision agriculture more accessible to smaller farms by exploring affordable hardware alternatives based on LoRaWAN technologies. This involves establishing a LoRaWAN test station at Hochschule Hof to test both affordable and expensive sensors variants in agricultural-like conditions for generating valuable data. The objective is to assess the practicality of using more economical sensor variants against their expensive counterparts and to develop a method for a data-driven comparative analysis of these sensors' performance in agricultural applications.
The conclusion of the thesis reveals that the LoRaWAN test station at Hochschule Hof successfully tested both affordable and expensive sensor variants. The affordable sensors effectively measured parameters like air temperature, humidity, and light intensity, but were less precise for scientific research in aspects like wind direction. Notable deviations in some weather and soil profile measurements indicate the necessity of additional studies. The research also evaluated the independent system set up at the university, noting its effectiveness and economic benefits compared to the Decentlab platform, albeit lacking in data visualization. Ultimately, the feasibility of replacing expensive sensors with affordable variants in precision agriculture was explored, with detailed findings and recommendations presented.
As we move deeper into the 21st century, the roles of artificial intelligence (AI) and robotics in shaping our world are becoming undeniably critical. These technologies stand at the cusp of transforming societal structures, enhancing life quality, and catalyzing human advancement in ways we've never seen before. It's essential to grasp the profound impact AI and robotics will have on our collective future. n terms of economic development and employment, AI and robotics are redefining industry norms through the automation of monotonous tasks, boosting of productivity levels, and minimization of costs. Despite worries about the potential loss of jobs, these innovations offer a silver lining by generating new roles in nascent fields like AI engineering, data analysis, and the development of interactive technologies between humans and machines. These are only a few examples. Therefore, the need for experts is constantly growing. In the course ‘applied robotics’ students implemented various projects, where they used state of the art methods from ai and robotics.
This book summarizes studies conducted by the Empirical Research and User Experience (ERUX) research group at the Institute for Information Systems (iisys) at Hof University of Applied Sciences over the period 2019 to 2022. The main topic focuses on “The Human-Machine-Interface in Advanced Driver Assistance Systems towards Autonomous Driving”, investigated using the example of automatic parking assistant in cars. A broad spectrum of methods was used to ensure comprehensive analyses and valid results.
Starting situation for the studies has been the industry's realization that the demand for parking assistants had fallen short of expectations. Moreover, they concluded that a host of driving assistant system owners´ do not use them. This indicates an unsatisfactory acceptance of new technologies on the part of car drivers. The aim of the studies was therefore to determine the reasons for this restraint, as well as to derive measures to increase acceptance of this systems among end customers.
The first study focused on operators and the restraint of German drivers towards driver assistance systems. The results of this quantitative study displayed that although the modernity of these systems has been identified, the functional enhancements they offer are insufficient. In order to overcome this discrepancy, manufacturers are advised to emphasize the functional advantages more strongly when communication with the end customer. Study also suggested that direct experience can significantly increase customers' willingness to purchase such a system. Therefore, it is of pivotal importance to introduce customers to the new technologies in a targeted manner.
Using conjoint measurement, a second study illustrates driver assistance systems already representing a significant benefit when purchasing a car, even though the trust in fully autonomous vehicles is still restricted. Drivers favor established car manufacturer in terms of the development of autonomous vehicles.
The third study utilizes eye-tracking to examine operating patterns of parking assistance systems. Moreover, it derives potential for improvement in terms of intuitive design and user experience.
Fourthly, alternative scenarios for the design of parking assistants are evaluated in a concept test. This indicated the vital importance of simple and acquainted operating options.
Across all methods, the customer actually being able to experience driving assistance systems is a decisive matter for the acceptance of these new technologies. Therefore, manufacturers should emphasize their focus on getting customers in touch with these systems, as well as offering them targeted usage options. In addition, the integration of customer feedback into development efforts is essential to produce intuitive, user-friendly user interfaces and thus promote the diffusion process of new technologies.
This paper is a collection of student projects, that have been carried out in the course artificial intelligence and robotics at the university of applied sciences Hof in the winter semester 2022. These projects bring together state of the art methods in ai and applications from the robotics domain.
Polyester fabrics are commonly dyed with the continuous disperse dyeing process and require a convection hot air dryer for drying and fixation of these fabrics. This convection hot air dryer is not only time-consuming compared to NIR drying but also energy intensive. For this reason, research was conducted to investigate if the newly developed advancedNIR® technology from Adphos Innovative Technologies GmbH is suitable for continuous disperse dyeing of polyester. There are specific parameters and temperatures which have been identified to help this technology be evaluated for its sustainable innovation potential for the textile industry. Eight disperse dyes were used from DyStar Colours Distribution GmbH, namely Dianix® XF2 (high energy) and Dianix® CC (medium energy). Trichromic colours (Dianix® Brown XF2/CC) have also been dyed to investigate the migration effect which was observed during the research. Different technology combinations were investigated for their potential application, especially spray application using rotating discs from Weitmann & Konrad GmbH & Co. KG / RotaSpray GmbH. These combined technologies could be a potential sustainable alternative process, which can be used in place of the convection hot air process, by replacing natural gas with electric power. Analysis of the final samples with optimized parameters shows improved levelness and fastness. Additional research is necessary to analyze the separate process steps in more detail.
According to a recent survey, 25% of respondents would prefer political decisions to be made by AI rather than flesh-and-blood politicians. Such a development would mark the end of an increasing mechanization of social processes, for which "digital" technologies such as AI and distributed ledgers (DLT) are primarily responsible. Regarding the impact that algorithms and digital automatisms have on our everyday life, one could argue that this may already have heralded the end of the anthropocene and the beginning of a posthuman age might be ahead.
The social sciences are currently discussing the influence of digitization on social decision-making through "algorithmic governance" in practical politics - with corresponding questions in the area of legitimacy and ethical justifiability of such, already practiced advances. In accordance to the much-cited "Internet of Things", this could lead to a "Governance of Things". The paper attempts to shed light on the technical nature of such an independent system. While AI is relevant for decision input, DLT methods can be used for decision execution. So-called "DAOs"are already applied in the economic sphere for the participation of autonomous systems as independent actors. However, a corresponding use in social decision-making raises new questions regarding legitimacy and representation and thus also about the relevance of human decision-making in the digital age: Which future is desirable and which development lead us into a dystopia? To what extent is it legitimate to expand technical achievements and push ahead with digital change? What are the challenges and how to face them?
The papers collected in this book represent the ideas exchanged during the 1st Conference of the Automation and Robotics Network Tunisia (ARNT2021) held from October 29 to October 31 in Sousse, Tunisia.
The papers fall into four categories:
1. Models: These papers present new model constructions and the rehabilitation of old in-house installations for teaching purposes. The propositions were selected with a view to the limited financial resources of the ISETs. Consequently, the papers provide a multitude of interesting impulses for low-cost implementation of teaching high-tech subjects.
2. Didactics: In this category the papers expose a flurry of learning approaches applied on automation and robotic subjects. The presented didactic methods are deduced from real teaching experiences.
3. Visions: These contributions introduce futuristic student projects which will need more than one iteration to be realized.
4. Study plan: In this session, the authors demonstrate the efficiency of their innovative ideas and discuss their integration on study plans.
Map matching is about finding the best route of a given track in a road network. This can be useful for many statistical analyses on mobility. With increasing spread of modern cars and mobile devices many tracks are available to match. The difficulty in map matching lies in the geospatial differences between tracks and road networks. Current technologies resolve such differences with Hidden Markov Models and Viterbi algorithm. They majorly vary concerning the used metrics for the probabilities in the models. In this research we improve map matching technology by refining the underlying algorithms, models and metrics. We will introduce Markov Decision Processes with Value Iteration and Q-Learning to the map matching domain and we will compare them to Hidden Markov Models with Viterbi algorithm. Markov Decision Processes allow to use active decisions and rewards, which are not available in previous methods. Combined with improvements concerning the preparation of tracks and the road network, and various technologies for improved processing speed, we will show on a publicly available map matching data set that our approach has a higher overall performance compared to previous map matching technology. We will eventually discuss more possibilities we enable with our approach.
The thesis takes a holistic view of Account-Based Marketing (ABM) program. It draws from the available literature about Account-based Marketing together with semi-structured expert interviews to answer the research question; What Organizational characteristics play an important role when implementing an Account-Based Marketing (ABM) program; that is; how can ABM be implemented successfully and what are the key success factors? From the findings, it is imperative for companies to focus on four key pillars in executing the program; Strategy, technology, people and processes. In finding a proper mix of these pillars across each maturity stage of the program, that is; being able to understand when to adjust the strategy, which technology to acquire, the right processes (ABM approach) to apply and at all times to keep the sales, marketing and delivery teams involved in harmony, companies will successfully execute the program. More so, the thesis provides a framework for companies that is; start-ups, small-medium and enterprises that are looking to apply the ABM program. In the aftermath of the COVID-19 pandemic, having meaningful value-adding relationships between buying and selling companies in the Business to Business (B2B) has become even more relevant. Applying an Account-based marketing strategy enables companies on both sides to achieve this.
This study examines the effects of medium-range influencer Instagram postings compared to traditional print ads. Using cosmetic products as an example, the study examines how these alternative forms of advertising influence attitude components and consumers' propensity to buy.
As a result, the advertising impact of the Instagram posting is lower than that of the classic print ad. The Instagram posting has its greatest effect where consumers already follow influencers (follower status).
The situational variable (type of advertising) proves to be more powerful in explaining consumers' attitudes as personal variables. Among the latter, product involvement has more explanatory power than the general personality traits of the Big Five. To explain the propensity to buy, product involvement is even more meaningful than the type of advertising. Overall, this shows that the effect of situational and personal factors on dependent variables of consumer behaviour cannot be generalised, but that it is generally recommended to include both situational and personal determinants in the analysis.
The Stability of Attitude and the Significance of Affective-emotional and Cognitive Components
(2018)
Research on attitude has a long tradition in marketing. It has commonly been assumed that attitudes are relatively stable over time. Contrary to this hypothesis, this paper shows that merely confronting consumers with some cognitive criteria concerning brand evaluation can in fact change their rating in the short term. A second finding is that evaluations of sportswear brands become consistently more negative when subjected to the cognitive evaluation process. A third result shows that purchasing behaviour can be explained to a greater extent by emotions than by cognitive components of attitude.
Although there is a numerous amount of literature on the effects of background music in advertising, we still lack empirical studies on the prerequisites and effects of audiobranding. The current paper deals with the question to which extent success of audio branding can be explained by several potential determinants. The success of audio branding is operationalised by measuring the level of aided and unaided recall of audio logos.
We distinguish between two categories of determinants: Firstly brand relatedpredictors such as fit between brand and audio logo.Secondly, according to the logic of market segmentation´s criteria, we derive personal-related predictors such as age and consumer´s musicality (i.e. sociodemographic), involvement (psychographic) and media use (behavioural).
The survey examines the coherence of such criteria with the recall of eight famous brands´ audio logos. As a result, all brand-related and personal-related predictors show weak but significant correlations with the recall of audio logos.
In the second step a multiple logistic regression analysis is performed to measure the contribution of each explanatory variable. Five out of seven predictors prove to be relevant for the success of audio branding.
Spatial Hypertext represents associations between chunks of information by spatial or visual attributes (such as proximity, color, shape etc.). This allows expressing information structures implicitly and in an intuitive way. However, automatic recognition of such informal, implicitly encoded structures by a machine (a so-called spatial parser) is still a challenge. One reason is, that conventional (non-adaptive) parsers are conceptually restricted by their underlying source of information (i. e., the spatial hypertext). Due to this limitation there are several types of structures that cannot be recognized properly. This inevitably limits both quality of parser output and parser performance. We claim that considering temporal aspects in addition to spatial and visual properties in spatial parser design will lead to significant increase in parsing accuracy, detection of richer structures and thus higher parser performance.
For the purpose of providing evidence, parsers for recognizing spatial, visual and temporal object relations have been implemented and tested in a series of user surveys. It turned out, that in none of the test cases pure spatial or visual parser could outperform the spatio-temporal parser. Instead, the spatiotemporal parser was able to compensate limitations of conventional parsers. Furthermore, differences in parsing accuracy were successfully tested for statistical significance. The results indicate a non-trivial effect that is recognizable by humans. We have shown that the addition of a temporal parser shifts machine detected structures significantly closer to what knowledge workers intend to express.
Analysis of Web 2.0 Technologies for Medical applications: Turning I-CAN into a collaborative tool
(2009)
1.1 Motivation I-CAN do it! That is the motto of the Centre for Disability Studies (CDS) and their instrument for the classification and assessment of support needs I-CAN. Since 2001, the CDS and partners are developing a tool to help support services to determine the current and future support needs of persons with disabilities. The current version 4.2 is the first web based tool and was introduced recently in 2008. However, the CDS is already looking ahead and is thinking about improvements for the following versions of their tool. With the huge success of Web 2.0 applications for the general use, also the health informatics sector got conscious of this technology and developed their own Web 2.0 tools. These applications, called Medicine 2.0 applications, are buzzwords in the health informatics community that appear in the press more and more often. In September 2008, the first Medicine 2.0 congress took place in Toronto, Canada and introduced the interesting concepts of Medicine 2.0 applications. The CDS is also interested in this development and is intererested in exploring how I-CAN can benefit from these new concepts. Their main concern is to empower persons with disabilities to get actively involved in their health care, according to the motto: I-CAN do it!
In recent years, companies discovered flash mobs as a unique way to promote their brand, a new product or service by combining virtual and live marketing communication strategies. In today’s world, where customers are targeted by several hundred advertising messages per day and where rejectionist attitudes and advertisement blindness is constantly increasing, flash mob marketing represents a promising direct interface between the customer and the business. Since flash mob marketing focuses on linking positive emotions and experiences to the organisers’ business, sophisticated flash mob marketing can become one of the most effective marketing strategies. It not only creates brand awareness, but also increases brand differentiation, brand loyalty and purchasing intentions. Furthermore, costs of the campaign remain relatively low if it is successful. Moreover, flash mob marketing can be adapted to different needs and is therefore suitable for any kind of business. Consequently, flash mob marketing represents a huge opportunity for businesses – regardless of a company’s available budget or its size.
However, if not well thought out, flash mob marketing bears also crucial risks: if the event fails to raise positive emotions within the target group, organisers will not only lose money but also risk creating long-term rejectionist feelings and attitudes, thus threatening their own brand or product. To avoid such an outcome, it is pivotal for the organising business to understand the environment of its target group – especially if the target group has another national and cultural background than the business itself. Therefore, this paper will deal with the question how culture- and country-specific differences impact the success of flash mob marketing campaigns, and highlights aspects which need to be considered in this context in the planning and execution of the event. The study is based on the examination of these exemplarily chosen countries: Germany, Indonesia and Mexico.