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Sowohl der stationäre Handel als auch die Online Pure Player befinden sich durch die zunehmende Digitalisierung und die Beeinflussung durch die dynamisch veränderten Trends in einem Wandel. Insbesondere wird von der Möbelbranche ein adaptives Verhalten an die vorliegenden Entwicklungen verlangt. Durch die Intensivierung der Markt- und Wettbewerbslandschaften und die Veränderungen des Verbraucherverhaltens bezüglich der verlangten Verschmelzung der Einkaufskanäle wird ein Umdenken gefordert und notwendig. Zusätzlich wird diese Notwendigkeit durch aktuelle Gegebenheiten, wie die Covid-19-Pandemie dringlicher. Die Omnichannel-Strategie und deren Etablierung birgt für die Möbelbranche insbesondere hinsichtlich der logistischen Herausforderungen Gelegenheiten und Bedrohungen. Diese sind zu erkennen, zu nutzen und zu beheben.
Big Data is now poised to mutate decision-making systems. Indeed, the decision is no longer based solely on the structured information that was hitherto collected and stored by the organization, but also on all data not structured outside the corporate straitjacket. The cloud and the information it contains impacts decisions and the industry is witnessing the emergence of business intelligence 3.0. With the growth of the internet, social networks, connected objects and communication information are now more abundant than ever before, along with rapid and substantial growth in their production. In 2012, 2.5 exabytes of data (one exabyte representing a million gigabytes of data) came every day to swell the ranks of big data (McAfee et al., 2012), which should weigh more than 40 zettabytes from 2020 (Valduriez, 2014) for 30 billion connected devices (The Internet Of Nothings, 2014) and 50 billion sensors (Davenport & Soulard, 2014). One of the most critical aspects of all of this information flow is the impact these will have on the way decisions are made. Indeed, in the part of an environment in which data was scarce and difficult to obtain, it was logical to let decision-making be conditioned by the intuition of the experienced decision-maker (Klein, Phillips, Rall, & Peluso, 2007). However, since information and knowledge are now available to everyone, the role of experts and decision-makers is gradually changing. Big data, in particular, makes it possible for analytical and decision-making systems to base their decision-making on global models. However, considering all the dimensions of the situations encountered, it was not until now that these systems were not within the reach of man, but were rationally limited (Simon & Newell, 1971). Big data and however, the processing of unstructured data requires modifying the architecture of decision support systems (DSS) of organizations. This paper is an inventory of developments undergone by aid systems decision-making, under the pressure of big data. Finally, it opens the debate on ethical questions raised by these new technologies, and it is observed that now, data analysis of personal data has become more debatable than in the past.
Bauprojekte sind in der Regel komplexe Vorhaben. Sie werden mit Hilfe des Projektmanagements und dessen Verfahren, Prozessen und Techniken bewältigt. Dennoch sind deutsche Bauprojekte nicht selten von Kosten- und Terminüberschreitungen betroffen. Ziel dieser Arbeit ist es, mögliche Optimierungsfelder im Planungs- und Steuerungsprozess eines Unternehmens für Industriebauprojekte zu identifizieren und darauf aufbauende Verbesserungsansätze zu erarbeiten. Um die Ziele verfolgen zu können, wurde eine qualitative Sozialforschung mittels Experteninterviews durchgeführt. Die Expertenaussagen verdeutlichen weiterhin Optimierungspotenzial, sowohl im Planungs- als auch im Steuerungsprozess. Ausgewählte Techniken (hauptsächlich aus dem klassischen Projektmanagement) dienen indessen dazu, die Effektivität und Effizienz des Planungsprozesses zu erhöhen. Innerhalb des Steuerungsprozesses zeigt sich, dass viele Optimierungsbereiche der Steuerung auf den Defiziten der Planung beruhen.
We present the concrete realization of a virtual laboratory equipped with a pedagogical agent. Its functionality and media didactics takes into account the results of an usability test on a prototype system, and the students' demand on such an automated assistance as obtained from a preliminary survey. The pedagogical agent mediates between the content and the learner by activating him or her. To provide information about the learner's skills, we propose a pragmatic and simplified competence model that is based on fundamental representations in physics (experiment, figure, text and equation). Moreover, an automated feedback relates the student's self-assessment with the submitted answer to the correctness of the respective task. In consequence, the pedagogical agent enables mental reflection for a crucial review of the own learning process. Interestingly, learning pathways can be envisioned, thus, giving valuable insight into individual strengths and weaknesses.
Modeling and executing knowledge-intensive processes (KiPs) are challenging with state-of-the-art approaches, and the specific demands of KiPs are the subject of ongoing research. In this context, little attention has been paid to the ontology-driven combination of data-centric and semantic business process modeling, which finds additional motivation by enabling the division of labor between humans and artificial intelligence. Such approaches have characteristics that could allow support for KiPs based on the inferencing capabilities of reasoners. We confirm this as we show that reasoners can infer the executability of tasks based on a currently researched ontology- and data-driven business process model (ODD-BP model). Further support for KiPs by the proposed inference mechanism results from its ability to infer the relevance of tasks, depending on the extent to which their execution would contribute to process progress. Besides these contributions along with the execution perspective (start-to-end direction), we will also show how our approach can help to reach specific process goals by inferring the relevance of process elements regarding their support to achieve such goals (end-to-start direction). The elements with the most valuable process progress can be identified in the intersection of both, the execution and goal perspective. This paper will introduce this new approach and verifies its practicability with an evaluation of a KiP in the field of emergency call centers.
For a detailed discussion of process mining, the objective of this paper is the analysis of the successful implementation of process mining in the practical fields of supply chain management. The research comprises the investigation of use cases in companies that are already actively using process mining.
Purpose: This research aims to highlight the applicability of process mining in the supply chain management business field.
Research Methodology: In order to examine the applicability of process mining in supply chain management a research study was conducted among experts in this business field. Further, theoretical findings were compared to the results and evaluated.
Results: Process Mining can be applied very well in the SCM area. The advantages that arise primarily reflect significant potential benefits and improved process throughput times. The information that can be gained from the operational areas supported by process mining is suitable for reliable decisions, both in the tactical and strategic areas.
Limitations: The results on the application of process mining show a certain generalization and have to be adapted and adjusted to the respective application case.
Contribution: This study is useful, especially for the purchasing and logistics business area.
Water is crucial for socio-economic development and healthy ecosystems. With the actual population growth and in view of future water scarcity, development calls for improved sectorial allocation of groundwater and surface water for domestic, agricultural and industrial use. Instead of intensifying the pressure on water resources, leading to conflicts among users and excessive pressure on the environment, sewage effluents, after pre-treatment, provide an alternative nutrient-rich water source for agriculture in the vicinity of cities. Water scarcity often occurs in arid and semiarid regions affected by droughts and large climate variability and where the choice of crop to be grown is limited by the environmental factors. Jatropha has been introduced as a potential renewable energy resource since it is claimed to be drought resistant and can be grown on marginal sites. Sewage effluents provide a source for water and nutrients for cultivating jatropha, a combined plant production/effluent treatment system. Nevertheless, use of sewage effluents for irrigation in arid climates carries the risk of salinization. Thus, potential irrigation with sewage effluents needs to consider both the water requirement of the crop and those needed for controlling salinity build-up in the top soil. Using data from a case study in Southern Morocco, irrigation requirements were calculated using CROPWAT 8.0. We present here crop evapotranspiration during the growing period, required irrigation, the resulting nutrient input and the related risk of salinization from the irrigation of jatropha with sewage effluent.
Introduction: Injury prevention programs (IPPs) are an inherent part of training in recreational and professional sports. Providing performance-enhancing benefits in addition to injury prevention may help adjust coaches and athletes’ attitudes towards implementation of injury prevention into daily routine. Conventional thinking by players and coaches alike seems to suggest that IPPs need to be specific to one’s sport to allow for performance enhancement. The systematic literature review aims to firstly determine the IPPs nature of exercises and whether they are specific to the sport or based on general conditioning. Secondly, can they demonstrate whether general, sports-specific or even mixed IPPs improve key performance indicators with the aim to better facilitate long-term implementation of these programs?
Methods: PubMed and Web of Science were electronically searched throughout March 2018. The inclusion criteria were randomized control trials, publication dates between Jan 2006 and Feb 2018, athletes (11–45 years), injury prevention programs and included predefined performance measures that could be categorized into balance, power, strength, speed/agility and endurance. The methodological quality of included articles was assessed with the Cochrane Collaboration assessment tools.
Results: Of 6619 initial findings, 22 studies met the inclusion criteria. In addition, reference lists unearthed a further 6 studies, making a total of 28. Nine studies used sports specific IPPs, eleven general and eight mixed prevention strategies. Overall, general programs ranged from 29–57% in their effectiveness across performance outcomes. Mixed IPPs improved in 80% balance outcomes but only 20–44% in others. Sports-specific programs led to larger scale improvements in balance (66%), power (83%), strength (75%), and speed/agility (62%).
Conclusion: Sports-specific IPPs have the strongest influence on most performance indices based on the significant improvement versus control groups. Other factors such as intensity, technical execution and compliance should be accounted for in future investigations in addition to exercise modality.
Thailand’s power system has been facing an energy transition due to the increasing amount of Renewable Energy (RE) integration, prosumers with self-consumption, and digitalization-based business models in a Local Energy Market (LEM). This paper introduces a decentralized business model and a possible trading platform for electricity trading in Thailand’s Micro-Grid to deal with the power system transformation. This approach is Hybrid P2P, a market structure in which sellers and buyers negotiate on energy exchanging by themselves called Fully P2P trading or through the algorithm on the market platform called Community-based trading. A combination of Auction Mechanism (AM), Bill Sharing (BS), and Traditional Mechanism (TM) is the decentralized price mechanism proposed for the Community-based trading. The approach is validated through a test case in which, during the daytime, the energy import and export of the community are significantly reduced when 75 consumers and 25 PV rooftop prosumers participate in this decentralized trading model. Furthermore, a comparison analysis confirms that the decentralized business model outperforms a centralized approach on community and individual levels.
Local biodiversity trends over time are likely to be decoupled from global trends, as local processes may compensate or counteract global change. We analyze 161 long-term biological time series (15–91 years) collected across Europe, using a comprehensive dataset comprising ~6,200 marine, freshwater and terrestrial taxa. We test whether (i) local long-term biodiversity trends are consistent among biogeoregions, realms and taxonomic groups, and (ii) changes in biodiversity correlate with regional climate and local conditions. Our results reveal that local trends of abundance, richness and diversity differ among biogeoregions, realms and taxonomic groups, demonstrating that biodiversity changes at local scale are often complex and cannot be easily generalized. However, we find increases in richness and abundance with increasing temperature and naturalness as well as a clear spatial pattern in changes in community composition (i.e. temporal taxonomic turnover) in most biogeoregions of Northern and Eastern Europe.
Background: High numbers of consumable medical materials (eg, sterile needles and swabs) are used during the daily routine of intensive care units (ICUs) worldwide. Although medical consumables largely contribute to total ICU hospital expenditure, many hospitals do not track the individual use of materials. Current tracking solutions meeting the specific requirements of the medical environment, like barcodes or radio frequency identification, require specialized material preparation and high infrastructure investment. This impedes the accurate prediction of consumption, leads to high storage maintenance costs caused by large inventories, and hinders scientific work due to inaccurate documentation. Thus, new cost-effective and contactless methods for object detection are urgently needed.
Objective: The goal of this work was to develop and evaluate a contactless visual recognition system for tracking medical consumable materials in ICUs using a deep learning approach on a distributed client-server architecture.
Methods: We developed Consumabot, a novel client-server optical recognition system for medical consumables, based on the convolutional neural network model MobileNet implemented in Tensorflow. The software was designed to run on single-board computer platforms as a detection unit. The system was trained to recognize 20 different materials in the ICU, while 100 sample images of each consumable material were provided. We assessed the top-1 recognition rates in the context of different real-world ICU settings: materials presented to the system without visual obstruction, 50% covered materials, and scenarios of multiple items. We further performed an analysis of variance with repeated measures to quantify the effect of adverse real-world circumstances.
Results: Consumabot reached a >99% reliability of recognition after about 60 steps of training and 150 steps of validation. A desirable low cross entropy of <0.03 was reached for the training set after about 100 iteration steps and after 170 steps for the validation set. The system showed a high top-1 mean recognition accuracy in a real-world scenario of 0.85 (SD 0.11) for objects presented to the system without visual obstruction. Recognition accuracy was lower, but still acceptable, in scenarios where the objects were 50% covered (P<.001; mean recognition accuracy 0.71; SD 0.13) or multiple objects of the target group were present (P=.01; mean recognition accuracy 0.78; SD 0.11), compared to a nonobstructed view. The approach met the criteria of absence of explicit labeling (eg, barcodes, radio frequency labeling) while maintaining a high standard for quality and hygiene with minimal consumption of resources (eg, cost, time, training, and computational power).
Conclusions: Using a convolutional neural network architecture, Consumabot consistently achieved good results in the classification of consumables and thus is a feasible way to recognize and register medical consumables directly to a hospital’s electronic health record. The system shows limitations when the materials are partially covered, therefore identifying characteristics of the consumables are not presented to the system. Further development of the assessment in different medical circumstances is needed.
The aim of this work was to develop and evaluate the reinforcement learning algorithm VentAI, which is able to suggest a dynamically optimized mechanical ventilation regime for critically-ill patients. We built, validated and tested its performance on 11,943 events of volume-controlled mechanical ventilation derived from 61,532 distinct ICU admissions and tested it on an independent, secondary dataset (200,859 ICU stays; 25,086 mechanical ventilation events). A patient “data fingerprint” of 44 features was extracted as multidimensional time series in 4-hour time steps. We used a Markov decision process, including a reward system and a Q-learning approach, to find the optimized settings for positive end-expiratory pressure (PEEP), fraction of inspired oxygen (FiO2) and ideal body weight-adjusted tidal volume (Vt). The observed outcome was in-hospital or 90-day mortality. VentAI reached a significantly increased estimated performance return of 83.3 (primary dataset) and 84.1 (secondary dataset) compared to physicians’ standard clinical care (51.1). The number of recommended action changes per mechanically ventilated patient constantly exceeded those of the clinicians. VentAI chose 202.9% more frequently ventilation regimes with lower Vt (5–7.5 mL/kg), but 50.8% less for regimes with higher Vt (7.5–10 mL/kg). VentAI recommended 29.3% more frequently PEEP levels of 5–7 cm H2O and 53.6% more frequently PEEP levels of 7–9 cmH2O. VentAI avoided high (>55%) FiO2 values (59.8% decrease), while preferring the range of 50–55% (140.3% increase). In conclusion, VentAI provides reproducible high performance by dynamically choosing an optimized, individualized ventilation strategy and thus might be of benefit for critically ill patients.
Background: Deficiency in musculoskeletal imaging (MI) education will pose a great challenge to physiotherapists in clinical decision making in this era of first-contact physiotherapy practices in many developed and developing countries. This study evaluated the nature and the level of MI training received by physiotherapists who graduate from Nigerian universities.
Methods: An online version of the previously validated Physiotherapist Musculoskeletal Imaging Profiling Questionnaire (PMIPQ) was administered to all eligible physiotherapists identified through the database of the Medical Rehabilitation Therapist Board of Nigeria. Data were obtained on demographics, nature, and level of training on MI procedures using the PMIPQ. Logistic regression, Friedman’s analysis of variance (ANOVA) and Kruskal-Wallis tests were used for the statistical analysis of collected data.
Results: The results (n = 400) showed that only 10.0% of the respondents had a stand-alone entry-level course in MI, 92.8% did not have any MI placement during their clinical internship, and 67.3% had never attended a MI workshop. There was a significant difference in the level of training received across MI procedures [χ2 (15) = 1285.899; p = 0.001]. However, there was no significant difference in the level of MI training across institutions of entry-level programme (p = 0.36). The study participants with transitional Doctor of Physiotherapy education were better trained in MI than their counterparts with a bachelor’s degree only (p = 0.047).
Conclusions: Most physiotherapy programmes in Nigeria did not include a specific MI module; imaging instructions were mainly provided through clinical science courses. The overall self-reported level of MI training among the respondents was deficient. It is recommended that stand-alone MI education should be introduced in the early part of the entry-level physiotherapy curriculum.
This paper describes the project “Visual Knowledge Communication”, a joint project that started recently. The partners are psychologists and computer scientists from four universities of the German state Rhineland-Palatinate. The starting point for the project was the fact that visualizations have attracted considerable interest in psychology as well as computer science within the last years. However, psychologists and computer scientists pursued their investigations independently from each other in the past. This project has as its main goal the support and fostering of cooperation between psychologists and computer scientists in several visualization research projects.
The paper sketches the overall project. It then discusses in more detail the authors' subproject which deals with a peer review process for animations developed by students. The basic ideas, the main goals, and the project plan are described.
This paper is a work-in-progress report. Therefore, it does not contain any results.
The study traces the development of compulsory vaccination in Germany against the background of political discussion and legislative activities, focusing on the area of tension between state health protection and the right to medical self-determination in the context of constitutional balancing. It is based on the assumption that the right to medical self-determination traditionally dominates state decisions in a democratic constitutional state and that the scope for decision-making is constantly being further contoured in the face of current challenges.
Study design: Systematic review with meta-analysis and meta-regression.
Background and objectives: We systematically reviewed and delineated the existing evidence on sustainability effects of motor control exercises on pain intensity and disability in chronic low back pain patients when compared with an inactive or passive control group or with other exercises. Secondary aims were to reveal whether moderating factors like the time after intervention completion, the study quality, and the training characteristics affect the potential sustainability effects.
Methods: Relevant scientific databases (Medline, Web of Knowledge, Cochrane) were screened. Eligibility criteria for selecting studies: All RCTs und CTs on chronic (≥ 12/13 weeks) nonspecific low back pain, written in English or German and adopting a longitudinal core-specific/stabilizing sensorimotor control exercise intervention with at least one pain intensity and disability outcome assessment at a follow-up (sustainability) timepoint of ≥ 4 weeks after exercise intervention completion.
Results and conclusions: From the 3,415 studies that were initially retrieved, 10 (2 CTs & 8 RCTs) on N = 1081 patients were included in the review and analyses. Low to moderate quality evidence shows a sustainable positive effect of motor control exercise on pain (SMD = -.46, Z = 2.9, p < .001) and disability (SMD = -.44, Z = 2.5, p < .001) in low back pain patients when compared to any control. The subgroups’ effects are less conclusive and no clear direction of the sustainability effect at short versus mid versus long-term, of the type of the comparator, or of the dose of the training is given. Low quality studies overestimated the effect of motor control exercises.
Intervention in the form of core-specific stability exercises is evident to improve trunk stability. The purpose was to assess the effect of an additional 6 weeks sensorimotor or resistance training on maximum isokinetic trunk strength and response to sudden dynamic trunk loading (STL) in highly trained adolescent athletes. The study was conducted as a single-blind, 3-armed randomized controlled trial. Twenty-four adolescent athletes (14f/10 m, 16 ± 1 yrs.;178 ± 10 cm; 67 ± 11 kg; training sessions/week 15±5; training h/week 22±8) were randomized into resistance training (RT; n=7), sensorimotor training (SMT; n = 10), and control group (CG; n = 7). Athletes were instructed to perform standardized, center-based training for 6 weeks, two times per week, with a duration of 1 h each session. SMT consisted of four different core-specific sensorimotor exercises using instable surfaces. RT consisted of four trunk strength exercises using strength training machines, as well as an isokinetic dynamometer. All participants in the CG received an unspecific heart frequency controlled, ergometer-based endurance training (50 min at max. heart frequency of 130HF). For each athlete, each training session was documented in an individual training diary (e.g., level of SMT exercise; 1RM for strength exercise, pain). At baseline (M1) and after 6 weeks of intervention (M2), participants’ maximum strength in trunk rotation (ROM:63°) and flexion/extension (ROM:55°) was tested on an isokinetic dynamometer (concentric/eccentric 30°/s). STL was assessed in eccentric (30°/s) mode with additional dynamometer-induced perturbation as a marker of core stability. Peak torque [Nm] was calculated as the main outcome. The primary outcome measurements (trunk rotation/extension peak torque: con, ecc, STL) were statistically analyzed by means of the two-factor repeated measures analysis of variance (α = 0.05). Out of 12 possible sessions, athletes participated between 8 and 9 sessions (SMT: 9 ± 3; RT: 8 ± 3; CG: 8 ± 4). Regarding main outcomes of trunk performance, experimental groups showed no significant pre–post difference for maximum trunk strength testing as well as for perturbation compensation (p > 0.05). It is concluded, that future interventions should exceed 6 weeks duration with at least 2 sessions per week to induce enhanced trunk strength or compensatory response to sudden, high-intensity trunk loading in already highly trained adolescent athletes, regardless of training regime.
The increasing availability of off-the-shelf high-frequency components makes radar measurement become popular in mainstream industrial applications. We present a cooperative FM radar for strongly reflective environments, being devised for a range of up to approx. 120 m. The target is designed with an unambiguous signature method and satisfies coherence. A prototype is built with commercial semiconductor components that operates in the 24 GHz industrial, scientific and medical band. First experimental results taken in sewage pipes are presented, using the target prototype and a standard FMCW radio station. An overview on four data acquisition procedures is given.
Background: Core-specific sensorimotor exercises are proven to enhance neuromuscular activity of the trunk, improve athletic performance and prevent back pain. However, the dose-response relationship and, therefore, the dose required to improve trunk function is still under debate. The purpose of the present trial will be to compare four different intervention strategies of sensorimotor exercises that will result in improved trunk function.
Methods/design: A single-blind, four-armed, randomized controlled trial with a 3-week (home-based) intervention phase and two measurement days pre and post intervention (M1/M2) is designed. Experimental procedures on both measurement days will include evaluation of maximum isokinetic and isometric trunk strength (extension/flexion, rotation) including perturbations, as well as neuromuscular trunk activity while performing strength testing. The primary outcome is trunk strength (peak torque). Neuromuscular activity (amplitude, latencies as a response to perturbation) serves as secondary outcome.
The control group will perform a standardized exercise program of four sensorimotor exercises (three sets of 10 repetitions) in each of six training sessions (30 min duration) over 3 weeks. The intervention groups’ programs differ in the number of exercises, sets per exercise and, therefore, overall training amount (group I: six sessions, three exercises, two sets; group II: six sessions, two exercises, two sets; group III: six sessions, one exercise, three sets). The intervention programs of groups I, II and III include additional perturbations for all exercises to increase both the difficulty and the efficacy of the exercises performed. Statistical analysis will be performed after examining the underlying assumptions for parametric and non-parametric testing.
Discussion: The results of the study will be clinically relevant, not only for researchers but also for (sports) therapists, physicians, coaches, athletes and the general population who have the aim of improving trunk function.
Background: Improving movement control might be a promising treatment goal during chronic non-specific low back pain (CLBP) rehabilitation. The objective of the study is to evaluate the effect of a single bout of game-based real-time feedback intervention on trunk movement in patients with CLBP.
Methods: Thirteen CLBP patients (8female;41 ± 16 years;173 ± 10 cm;78 ± 22 kg) were included in this randomized cross-over pilot trial. During one laboratory session (2 h), participants performed three identical measurements on trunk movement all including: first, maximum angle of lateral flexion was assessed. Secondly, a target trunk lateral flexion (angle: 20°) was performed. Main outcome was maximum angle ([°]; MA). Secondary outcomes were deviation [°] from the target angle (angle reproduction; AR) and MA of the secondary movement planes (rotation; extension/flexion) during lateral flexion. The outcomes were assessed by an optical 3D-motion-capture-system (2-segment-trunk-model). The measurements were separated by 12-min of intervention and/or resting (randomly). The intervention involved a sensor-based trunk exergame (guiding an avatar through virtual worlds). After carryover effect-analysis, pre-to-post intervention data were pooled between the two sequences followed by analyses of variances (paired t-test).
Results: No significant change from pre to post intervention for MA or AR for any segment occurred for the main movement plane, lateral flexion (p > .05). The upper trunk segment showed a significant decrease of the MA for trunk extension/flexion from pre to post intervention ((4.4° ± 4.4° (95% CI 7.06–1.75)/3.5° ± 1.29° (95% CI 6.22–0.80); p = 0.02, d = 0.20).
Conclusions: A single bout of game-based real-time feedback intervention lead to changes in the secondary movement planes indicating reduced evasive motion during trunk movement.