Der Six-Sigma-Ansatz und dessen Implementierung aus Sicht einer Sparkasse: Eine Darstellung und Analyse

Der Six-Sigma-Ansatz dient dem strategischen Management der Prozessverbesserung, der neben einem statistischen Qualitätsziel zugleich eine Methode des Qualitätsmanagement umfasst. Während es sich in Industrieunternehmen seit längerem etabliert hat, ist dieses Konzept in der Finanzwelt, jedenfalls in Deutschland, bislang verhalten aufgegriffen worden. Die vorliegende Studie befasst sich mit den Möglichkeiten und Grenzen des Einsatzes bei Kreditinstituten. In Rahmen der anwendungsorientierten Überlegungen wird vor allem die Implementierung am Beispiel einer Modellsparkasse geprüft. Daraus lassen sich Handlungsund Gestaltungsempfehlungen ableiten.The Six Sigma approach serves the strategical management of process improvement, which encloses not only a statistical high class aim, but also a method for high class quality management. While it has established itself in industrial enterprises for a while now, this concept has been taken up with much reservation in the financial world, at least in Germany. The present study addresses the possibilities and limits of application of this concept at credit institutions.The implementation is tested on an example at a model savings bank under the application-oriented considerations. Guidances and design recommendations can be derived from this

Increased levels of anti-glycan antibodies in patients with cystic fibrosis

<p>Abstract</p> <p>Background</p> <p>The prevalence of Crohn's disease (CD) is increased in patients with cystic fibrosis (CF). Anti-Saccharomyces cerevisiae antibodies (ASCA) have been suggested as a screening tool to detect CD in CF. Recently, several new anti-glycan antibodies have been reported in CD.</p> <p>Materials and methods</p> <p>The sera of 119 CF patients of various age groups were prospectively screened for ASCA type IgG (gASCA), anti-laminaribioside carbohydrate IgG antibodies (ALCA), anti-chitobioside carbohydrate IgA antibodies (ACCA), and anti-mannobioside carbohydrate IgG antibodies (AMCA). The frequency of these anti-glycan antibodies was then compared in patients with CD, ulcerative colitis, rheumatoid arthritis and healthy volunteers.</p> <p>Results</p> <p>A significant number of CF patients were positive for gASCA (51.3% [41.6-60.6]) and up to three other anti-glycan antibodies concurrently. Serum levels of anti-glycan antibodies in CF and CD were not related to parameters of inflammation. Despite the well-documented difference in clinical course between male and female CF patients no gender difference of anti-glycan antibodies was found. In contrast, there was a significant positive correlation between anti-glycan markers and age in CF patients.</p> <p>Conclusions</p> <p>Our findings demonstrate for the first time the increased frequency of a panel of anti-glycan antibodies in CF and provide a link between the presence of these serological biomarkers and patient's age. Anti-glycan antibody profiling may therefore become a valuable tool in the care of patients with CF.</p

Digestive enzymes of copepodids and adults of Calanus finmarchicus and C. helgolandicus in relation to particulate matter

During spring and in summer the digestive enzymes trypsin and amylase of copepodids and adults of Calanus finmarchicus and C. helgolandicus were studied in a Swedish fjord in relation to various parameters of particulate matter. Regulation mechanisms of digestive enzymes varied with stage of development and physiological condition. In the stages studied three types of regulation were found: In copepodid stages Cl/II trypsin remained constant at a rather high activity irrespective of variations in amylase activity; in CIII-CV and males trypsin and amylase were strongly correlated; in females both enzymes varied independently of each other. Digestive enzymes of CV, females and males of the overwintering generation, were generally very low and did not correlate with any of the food parameters. The digestive enzyme activities were compared with concentrations of chlorophyll a, particulate carbon, nitrogen and carbohydrates at different depths. Amylase of stages CI-CV and adult males and trypsin of CIII-CV and males correlated significantly with carbohydrate concentrations. On the other hand amylase of adult females gave significant correlations with chlorophyll a and carbon. It is suggested that this difference between females and the other stages indicates different food selection

Average Communication Rate for Networked Event-Triggered Stochastic Control Systems

Quantifying the average communication rate (ACR) of a networked event-triggered stochastic control system (NET-SCS) with deterministic thresholds is a challenging problem due to the non-stationary nature of the system's stochastic processes. For such a system, a closed-loop effect emerges due to the interdependence between the system variable and the trigger of communication. This effect, commonly referred to as \textit{side information} by related work, distorts the stochastic distribution of the system variables and makes the ACR computation non-trivial. Previous work in this area used to over-simplify the computation by ignoring the side information and misusing a Gaussian distribution, which leads to approximated results. This paper proposes both analytical and numerical approaches to predict the exact ACR for a NET-SCS using a recursive model. Furthermore, we use theoretical analysis and a numerical study to qualitatively evaluate the deviation gap of the conventional approach that ignores the side information. The accuracy of our proposed method, alongside its comparison with the simplified results of the conventional approach, is validated by experimental studies. Our work is promising to benefit the efficient resource planning of networked control systems with limited communication resources by providing accurate ACR computation

When Offline Stores Reduce Online Returns

Among the dark sides of contemporary multi-channel retailing are the vast amounts of product returns, especially in the online channel. High product returns not only put pressure on the retailers' profitability, but also come at high societal and environmental costs. A central question then is whether multi-channel retailers can use their offline stores to help reduce product returns in the online channel without harming online sales. In an empirical study, we address this issue using data from a large Dutch shoe retailer. We develop a novel spatial model to estimate the influence of proximate retail stores on customers' online shopping behavior, while controlling for spatial and customer heterogeneity. Results demonstrate that an increased offline channel presence indeed reduces online returns, depending on the product's risk profile, without significantly lowering online sales. Offline stores can thus be an effective and appealing way for retailers to mitigate the negative impact of online shopping related to product returns

Delay-sensitive Joint Optimal Control and Resource Management in Multi-loop Networked Control Systems

In the operation of networked control systems, where multiple processes share a resource-limited and time-varying cost-sensitive network, communication delay is inevitable and primarily influenced by, first, the control systems deploying intermittent sensor sampling to reduce the communication cost by restricting non-urgent transmissions, and second, the network performing resource management to minimize excessive traffic and eventually data loss. In a heterogeneous scenario, where control systems may tolerate only specific levels of sensor-to-controller latency, delay sensitivities need to be considered in the design of control and network policies to achieve the desired performance guarantees. We propose a cross-layer optimal co-design of control, sampling and resource management policies for an NCS consisting of multiple stochastic linear time-invariant systems which close their sensor-to-controller loops over a shared network. Aligned with advanced communication technology, we assume that the network offers a range of latency-varying transmission services for given prices. Local samplers decide either to pay higher cost to access a low-latency channel, or to delay sending a state sample at a reduced price. A resource manager residing in the network data-link layer arbitrates channel access and re-allocates resources if link capacities are exceeded. The performance of the local closed-loop systems is measured by a combination of linear-quadratic Gaussian cost and a suitable communication cost, and the overall objective is to minimize a defined social cost by all three policy makers. We derive optimal control, sampling and resource allocation policies under different cross-layer awareness models, including constant and time-varying parameters, and show that higher awareness generally leads to performance enhancement at the expense of higher computational complexity

Physically interacting humans regulate muscle coactivation to improve visuo-haptic perception.

When moving a piano or dancing tango with a partner, how should I control my arm muscles to sense their movements and follow or guide them smoothly? Here we observe how physically connected pairs tracking a moving target with the arm modify muscle coactivation with their visual acuity and the partner's performance. They coactivate muscles to stiffen the arm when the partner's performance is worse and relax with blurry visual feedback. Computational modeling shows that this adaptive sensing property cannot be explained by the minimization of movement error hypothesis that has previously explained adaptation in dynamic environments. Instead, individuals skillfully control the stiffness to guide the arm toward the planned motion while minimizing effort and extracting useful information from the partner's movement. The central nervous system regulates muscle activation to guide motion with accurate task information from vision and haptics while minimizing the metabolic cost. As a consequence, the partner with the most accurate target information leads the movement.NEW & NOTEWORTHY Our results reveal that interacting humans inconspicuously modulate muscle activation to extract accurate information about the common target while considering their own and the partner's sensorimotor noise. A novel computational model was developed to decipher the underlying mechanism: muscle coactivation is adapted to combine haptic information from the interaction with the partner and own visual information in a stochastically optimal manner. This improves the prediction of the target position with minimal metabolic cost in each partner, resulting in the lead of the partner with the most accurate visual information

Fast IMU-based Dual Estimation of Human Motion and Kinematic Parameters via Progressive In-Network Computing

Many applications involve humans in the loop, where continuous and accurate human motion monitoring provides valuable information for safe and intuitive human-machine interaction. Portable devices such as inertial measurement units (IMUs) are applicable to monitor human motions, while in practice often limited computational power is available locally. The human motion in task space coordinates requires not only the human joint motion but also the nonlinear coordinate transformation depending on the parameters such as human limb length. In most applications, measuring these kinematics parameters for each individual requires undesirably high effort. Therefore, it is desirable to estimate both, the human motion and kinematic parameters from IMUs. In this work, we propose a novel computational framework for dual estimation in real-time exploiting in-network computational resources. We adopt the concept of field Kalman filtering, where the dual estimation problem is decomposed into a fast state estimation process and a computationally expensive parameter estimation process. In order to further accelerate the convergence, the parameter estimation is progressively computed on multiple networked computational nodes. The superiority of our proposed method is demonstrated by a simulation of a human arm, where the estimation accuracy is shown to converge faster than with conventional approaches