Advanced product planning: a comprehensive process for systemic definition of new product requirements

This paper reports results of research into the definition of requirements for new consumer products––specifically, electro-mechanical products. The research dealt with the derivation of design requirements that are demonstrably aligned with stakeholder needs. The paper describes a comprehensive process that can enable product development teams to deal with statements of product requirements, as originally collected through market research activities, in a systematic and traceable manner from the early, fuzzy front end, stages of the design process. The process described has been based on principles of systems engineering. A case study from its application and evaluation drawn from the power sector is described in this paper. The case study demonstrates how the process can significantly improve product quality planning practices through revision of captured product requirements, analysis of stakeholder requirements and derivation of design requirements. The paper discusses benefits and issues from the use of the process by product development teams, and identifies areas for further research. Finally, the conclusions drawn from the reported research are presented.

通过在线客户体验来推动销售

21世纪的消费者在消费体验方面更有自己的主张,直复营销也有了发展。尤其是那些已推出在线业务的企业,已有能力与个人进行互动。     

Unsupervised and simultaneous training of multiple object detectors from unlabeled surveillance video

Object detection is an essential component in automated vision-based surveillance systems. In general, object detectors are constructed using training examples obtained from large annotated data sets. The inevitable limitations of typical training data sets make such supervised methods unsuitable for building generic surveillance systems applicable to a wide variety of scenes and camera setups. In our previous work we proposed an unsupervised method for learning and detecting the dominant object class in a general dynamic scene observed by a static camera. In this paper, we investigate the possibilities to expand the applicability of this method to the problem of multiple dominant object classes. We propose an idea on how to approach this expansion, and perform an evaluation of this idea using two representative surveillance video sequences.     

Integrating scientific modeling and supporting dynamic hazard management with a GeoAgent-based representation of human–environment interactions: A drought example in Central Pennsylvania, USA

Recent natural disasters indicate that modern technologies for environmental monitoring, modeling, and forecasting are not well integrated with cross-level social responses in many hazard-management systems. This research addresses this problem through a Java-based multi-agent prototype system, GeoAgent-based Knowledge System (GeoAgentKS). This system allows: (1) computer representation of institutional regulations and behavioral rules used by multiple social institutions and individuals in cross-level human–environment interactions, (2) integration of this representation with scientific modeling of dynamic hazard development, and (3) application of automated reasoning that suggests to users the appropriate actions for supporting cooperative social responses. This paper demonstrates the software architecture of GeoAgentKS and presents such an integrated approach by modeling the drought management processes in Central Pennsylvania, USA. The results show that it is possible to use GeoAgentKS to represent multilevel human–environment interactions and to use those interactions as input to decision making in hazard management.     

Business process management with the user requirements notation

A number of recent initiatives in both academia and industry have sought to achieve improvements in e-businesses through the utilization of Business Process Management (BPM) methodologies and tools. However there are still some inadequacies that need to be addressed when it comes to achieving alignment between business goals and business processes. The User Requirements Notation (URN), recently standardized by ITU-T, has some unique features and capabilities beyond what is available in other notations that can help address alignment issues. In this paper, a URN-based framework and its supporting toolset are introduced which provide business process monitoring and performance management capabilities integrated across the BPM lifecycle. The framework extends the URN notation with Key Performance Indicators (KPIs) and other concepts to measure and align processes and goals. An example process for controlling access to a healthcare data warehouse is used to illustrate and evaluate the framework. Early results indicate the feasibility of the approach.     

A taxonomy for and analysis of multi-person-display ecosystems

Interactive displays are increasingly being distributed in a broad spectrum of everyday life environments: they have very diverse form factors and portability characteristics, support a variety of interaction techniques, and can be used by a variable number of people. The coupling of multiple displays creates an interactive “ecosystem of displays”. Such an ecosystem is suitable for particular social contexts, which in turn generates novel settings for communication and performance and challenges in ownership. This paper aims at providing a design space that can inform the designers of such ecosystems. To this end, we provide a taxonomy that builds on the size of the ecosystem and on the degree of individual engagement as dimensions. We recognize areas where physical constraints imply certain kinds of social engagement, versus other areas where further work on interaction techniques for coupling displays can open new design spaces.     

Scheduling algorithms for fault-tolerance in hard-real-time systems

Many time-critical applications require predictable performance in the presence of failures. This paper considers a distributed system with independent periodic tasks which can checkpoint their state on some reliable medium in order to handle failures. The problem of preemptively scheduling a set of such tasks is discussed where every occurrence of a task has to be completely executed before the next occurrence of the same task can start. Efficient scheduling algorithms are proposed which yield sub-optimal schedules when there is provision for fault-tolerance. The performance of the solutions proposed is evaluated in terms of the number of processors and the cost of the checkpoints needed. Moreover, analytical studies are used to reveal interesting trade-offs associated with the scheduling algorithms.This work has been supported by grants from the Italian Ministero dell'Università e della Ricerca Scientifica e Tecnologica and the Consiglio Nazionale delle Ricerche-Progetto Finalizzato Sistemi Informatici e Calcolo Parallelo.     

Occluded Video Instance Segmentation: A Benchmark

International Journal of Computer Vision - Can our video understanding systems perceive objects when a heavy occlusion exists in a scene? To answer this question, we collect a large-scale dataset...     

Hyperprolactinemia in end‐stage renal disease and effects of frequent hemodialysis

Introduction: End‐stage renal disease is associated with elevations in circulating prolactin concentrations, but the association of prolactin concentrations with intermediate health outcomes and the effects of hemodialysis frequency on changes in serum prolactin have not been examined. Methods: The FHN Daily and Nocturnal Dialysis Trials compared the effects of conventional thrice weekly hemodialysis with in‐center daily hemodialysis (6 days/week) and nocturnal home hemodialysis (6 nights/week) over 12 months and obtained measures of health‐related quality of life, self‐reported physical function, mental health and cognition. Serum prolactin concentrations were measured at baseline and 12‐month follow‐up in 70% of the FHN Trial cohort to examine the associations among serum prolactin concentrations and physical, mental and cognitive function and the effects of hemodialysis frequency on serum prolactin. Findings: Among 177 Daily Trial and 60 Nocturnal Trial participants with baseline serum prolactin measurements, the median serum prolactin concentration was 65 ng/mL (25th–75th percentile 48–195 ng/mL) and 81% had serum prolactin concentrations >30 ng/mL. While serum prolactin was associated with sex (higher in women), we observed no association between baseline serum prolactin and age, dialysis vintage, and baseline measures of physical, mental and cognitive function. Furthermore, there was no significant effect of hemodialysis frequency on serum prolactin in either of the two trials. Discussion: Serum prolactin concentrations were elevated in the large majority of patients with ESRD, but were not associated with several measures of health status. Circulating prolactin levels also do not appear to decrease in response to more frequent hemodialysis over a one‐year period.