Quantifying knowledge complexity

One of the many contributions of the paper of Goldwasser, Micali and Rackoff is the introduction of the notion of knowledge complexity. Knowledge complexity zero (also known as zero-knowledge) has received most of the attention of the authors and all the attention of their followers. In this paper, we present several alternative definitions of knowledge complexity and investigate the relations between them. Received: July 22, 1997.     

Causal design knowledge: Alternative representation method for product development knowledge management

This paper presents a mathematical comparison of procedural knowledge and causal knowledge, and discusses the potential roles and feasibility of causal knowledge across product development knowledge management. Since reuse of knowledge is so important in product development, various knowledge management approaches have been introduced. Most of the product design knowledge is represented by procedural knowledge, which unfortunately requires cumbersome processes to define, and is typically inadequate for representing the kind of knowledge generated during the product development process. A causal knowledge representation, however, can help us to overcome this limitation and is an alternative formalism for representing product design knowledge. In this paper we compare the procedural and causal knowledge representations. We present the mathematical definitions of two knowledge paradigms, then mathematically describe the relationship between the two. Both knowledge paradigms are then compared based on the perspective of knowledge expression, decision alternative representation, reasoning capability, and knowledge cultivation. This paper concludes that causal knowledge representation is superior to procedural knowledge representation based on the four perspectives. Finally, the knowledge systems are modeled using Systems Modeling Language (SysML), and we present a case study that demonstrates the causal knowledge features using a realistic example from industry.     

Complex organizational knowledge structures for new product development teams

When a new product development team faces challenges, such as the cross-functional knowledge conversion task, both simple and existing organizational structures are comprised of various management methods and knowledge characteristics, analogous to a fully armed military force. However, these features are not arranged in order of priority. Each step within the knowledge conversion process of new product development may not require such a full depot of management methods and keynotes. Therefore, this study adopted Blackler’s perspective to examine the suitable organizational knowledge structure for cross-functional knowledge conversion within new product development teams.This study found that the continual steps of socialization, externalization, combination, and internalization in the new product development team’s knowledge conversion process were positively related to various organizational knowledge structures based on a survey of 107 Taiwanese high-technology small and medium-sized enterprises’ new product development teams – not merely a simple structure for all steps. Thus, these results confirm that complex structures are required to perform knowledge conversion. Socialization requires knowledge characteristics from both the communication-intensive organization and the symbolic-analyst-dependent organization. Externalization requires elements of knowledge from the communication-intensive organization, the symbolic-analyst-dependent organization, and knowledge-routinized organization. Combination requires features from the knowledge-routinized organization, and internalization requires characteristics from the expert-dependent organization.In addition, this study attempted to integrate the knowledge features from communication-intensive organization and symbolic-analyst-dependent organization structures for the socialization and externalization stages. This effort concentrated on solving novel and irregular problems through a simplification of the complex organizational structures which make the new product development’s knowledge conversion run smoother.     

Mining demand chain knowledge of life insurance market for new product development

Demand chain management (DCM) can be defined as “extending the view of operations from a single business unit or a company to the whole chain. Essentially, demand chain management focuses not only on generating drawing power from customers to purchase merchandises on the supply chain; but also on exploring satisfaction, participation, and involvement from customers in order for enterprises to understand customer needs and wants. Thus, customers have changed their position in the demand chain to assume a leading role in bringing more benefit for enterprises. This article investigates what functionalities best fit the consumers’ needs and wants for life insurance products by extracting specific knowledge patterns and rules from consumers and their demand chain. By doing so, this paper uses the a priori algorithm and clustering analysis as methodologies for data mining. Knowledge extraction from data mining results is illustrated as market segments and demand chain analysis on life insurance market in Taiwan in order to propose suggestions and solutions to the insurance firms for new product development and marketing.     

Quantifying forecast quality of IT business value

This article discusses how to quantify the forecasting quality of IT business value. We address a common economic indicator often used to determine the business value of project proposals, the Net Present Value (NPV). To quantify the forecasting quality of IT business value, we develop a generalized method that is able to account for asymptotic cases and negative valued entities. We assess the generalization with real-world data of four organizations together consisting of 1435 IT assets with a total investment cost of 1232+ million Euro for which 6328 forecasts were made. Using the generalized method, we determine the forecasting quality of the NPV, along with the benefits and cost using real-world data of another 102 IT assets with a total business value of 1812 million Euro. For the real-world case study, we will find that the quality of the forecasted NPVs is lower than the forecasted benefits, which is again lower than the forecasting quality of the cost. Also, we perform a sensitivity analysis to investigate the impact on the quality of an asset’s forecasted NPV when the forecasting quality of benefits or cost improves. Counterintuitively, it turned out in this case study that if the quality of cost forecasts would improve, the overall quality of its NPV predictions would degrade. This underlines the importance of both accurate cost and benefit predictions. Finally, we show how to use the quantified forecast information to enhance decision information using two simulation examples.     

Scalable access within the context of digital libraries

This paper presents a summary of some of the work-in-progress within the Alexandria Digital Library Project. In particular, we present scalable methods for locating information at different levels within a distributed digital library environment. Starting at the high level, we show how queries can be routed to appropriate information sources. At a given source, efficient query processing is supported by using materialized views and multidimensional index structures. Finally, we propose solutions to the problem of storage and retrieval of large objects on both secondary and tertiary storage devices.     

KnowledgeScope: managing knowledge in context

Knowledge repositories have been implemented in many organizations, but they often suffer from non-use. This research considers two key design factors that cause non-use: the extra burden on users to document knowledge in the repository, and the lack of a standard knowledge structure that facilitates knowledge sharing among users with different perspectives. We propose a design of a knowledge management system called KnowledgeScope that addresses these problems through (1) an integrated workflow support capability that captures and retrieves knowledge as an organizational process proceeds, i.e., within the context in which it is created and used, and (2) a process meta-model that organizes that knowledge and context in a knowledge repository. In this paper, we describe this design and report the results from implementing it in a real-life organization.     

A dynamic decision support system to predict the value of customer for new product development

In recent years, firms have focused on how to enter markets and meet customer requirements by improving product attributes and processes to boost their market share and profits. Consequently, market-driven product design and development has become a popular topic in the literature. However, past research neither covers all of the major influencing factors that together drive customers to make purchase decisions, nor connects these various influencing factors to customer purchasing behavior. Past studies further fail to take the time value of money and customer value into consideration. This study proposes a decision support system to (a) predict customer purchasing behavior given certain product, customer, and marketing influencing factors, and (b) estimate the net customer lifetime value from customer purchasing behavior toward a specific product. This will not only enable decision-makers to compare alternatives and select competitive products to launch on the market, but will also improve the understanding of customer behavior toward particular products for the formulation of effective marketing strategies that increase customer loyalty and generate greater profits in the long term. Decision-makers can also make use of the system to build up confidence in new product development in terms of idea generation and product improvement. The application of the proposed system is illustrated and confirmed to be sensible and convincing through a case study.     

Utilizing knowledge context in virtual collaborative work

The understanding of knowledge can be impaired if it is isolated from the proper context. Despite the importance of contextual information, there has been limited support for utilizing context in current knowledge management and collaborative systems. This paper presents a knowledge context model, called KC-V, which facilitates the use of contextual information in virtual collaborative work. Four benefits of using KC-V are suggested: evolutionary accumulation of knowledge aligned with collaborative activities, supporting the virtual team lifecycle, improved understanding by rich navigation paths, and searching for knowledge with similar context. A web-based collaboration system called VWSS is developed using KC-V.     

Issues for integrating knowledge in new product development: reflections from an empirical study

With increased market pressures now imposed on companies there is a greater requirement for information and knowledge to be considered as fundamental resources; the need to rapidly provide high quality products of high performance and reliability is forcing companies to change the way in which they manage them. The goal of this paper is to identify the pertinent research issues that will need to be considered in order for knowledge (and information) to be successfully integrated into future product development. This will be achieved by presenting the key findings from empirical and simulation studies of information and knowledge access in engineering design, within a number of different design activities. In particular, this will show the extent to which engineers rely on their personal knowledge.     

A knowledge system for integrated product design

This paper discusses the architecture and implementation issues for a knowledge system to assist in product design. The goals of the concurrent Design Advisor (CODA) are to enhance the quality of designs by 25 percent and the efficiency by a factor of 10. The improvement springs from the integration of diverse knowledge bases, ranging from customer needs to product evaluation, and from process configuration to production control. One source of efficiency is the automation of many routine tasks, thereby increasing user productivity. Another source is the increase in the quality of initial designs, which obviates the need for numerous iterations in the design process due to poor manufacturability. CODA is based on the general architecture of the Creativity Support System, an expert system for assisting users in specific domains requiring creative solutions. The bilevel structure of the system consists of a domain-independent module containing general tools and techniques for creative problem-solving, and a domain-dependent module incorporating knowledge specific to particular fields of application. The utility of this approach is illustrated in the realm of concurrent product design by demonstrating a CODA within the general architecture of the system.     

Quantifying structural attributes of system decompositions in 28 feature-oriented software product lines

A key idea of feature orientation is to decompose a software product line along the features it provides. Feature decomposition is orthogonal to object-oriented decomposition—it crosscuts the underlying package and class structure. It has been argued often that feature decomposition improves system structure by reducing coupling and by increasing cohesion. However, recent empirical findings suggest that this is not necessarily the case. In this exploratory, observational study, we investigate the decompositions of 28 feature-oriented software product lines into classes, features, and feature-specific class fragments. The product lines under investigation are implemented using the feature-oriented programming language Fuji. In particular, we quantify and compare the internal attributes import coupling and cohesion of the different product-line decompositions in a systematic, reproducible manner. For this purpose, we adopt three established software measures (e.g., coupling between units, CBU; internal-ratio unit dependency, IUD) as well as standard concentration statistics (e.g., Gini coefficient). In our study, we found that feature decomposition can be associated with higher levels of structural coupling in a product line than a decomposition into classes. Although coupling can be concentrated in very few features in most feature decompositions, there are not necessarily hot-spot features in all product lines. Interestingly, feature cohesion is not necessarily higher than class cohesion, whereas features are more equal in serving dependencies internally than classes of a product line. Our empirical study raises critical questions about alleged advantages of feature decomposition. At the same time, we demonstrate how our measurement approach of coupling and cohesion has potential to support static and dynamic analyses of software product lines (i.e., type checking and feature-interaction detection) by facilitating product sampling.     

传感网环境下视频传感器在线规划

针对视频传感器观测被动的问题,结合视频传感器和传感网的特点,设计了传感网环境下视频传感器在线规划框架。该框架采用面向服务的体系架构（ SOA）,包含资源层、资源服务层、规划服务层和应用层四个层,各层之间采用标准的网络通信协议进行通信。实现了视频传感器在线规划原型系统,并以视频监控签到为应用场景进行了在线规划实验。实验结果表明：该框架对于实现视频传感器主动和按需观测是可行且有效的。     

The value of storyboards in the product design process

In the realm of product design, communication between designer, client, design team and future users is of great importance. Throughout the design process, ideas and concepts are generated and must be conveyed to these people to evoke comments, judgement or acceptance, depending on the process phase. Storyboards are a valuable aid to the designer in this task by providing a common visual language that people from different backgrounds can ‘read’ and understand. However, the visualisation style of the storyboards influences the reactions. Where open and sketchy storyboards are inviting comments, sleek and detailed presentations can be overwhelming. Storyboards not only help the product designer to get a grip on target groups, context, product use and timing, but also in communicating about these aspects with all people involved. This paper is part of the 3AD design colloquium Creative connections [1].     

Integrating virtual and physical context to support knowledge workers

The Kimura system augments and integrates independent tools into a pervasive computing system that monitors a user's interactions with the computer, an electronic whiteboard, and a variety of networked peripheral devices and data sources.     

SPI success factors within product usability evaluation

This article presents an experience report where we compare 8 years of experience of product related usability testing and evaluation with principles for software process improvement (SPI). In theory the product and the process views are often seen to be complementary, but studies of industry have demonstrated the opposite. Therefore, more empirical studies are needed to understand and improve the present situation. We find areas of close agreement as well as areas where our work illuminates new characteristics. It has been identified that successful SPI is dependent upon being successfully combined with a business orientation. Usability and business orientation also have strong connections although this has not been extensively addressed in SPI publications. Reasons for this could be that usability focuses on product metrics whilst today's SPI mainly focuses on process metrics. Also because today's SPI is dominated by striving towards a standardized, controllable, and predictable software engineering process; whilst successful usability efforts in organisations are more about creating a creative organisational culture advocating a useful product throughout the development and product life cycle. We provide a study and discussion that supports future development when combining usability and product focus with SPI, in particular if these efforts are related to usability process improvement efforts.     

Analysis of collectivism and egoism phenomena within the context of social welfare

Comparative benefits provided by basic social strategies, i.e., collectivism and egoism, are investigated within the framework of democratic collective decisions.     

On the development of a haptic system for rapid product development

This paper presents a system development that extends haptic modeling to a number of key aspects in product development. Since haptic modeling has been developed based on physical laws, it is anticipated that a natural link between the virtual world and practical applications can be established based on haptic interaction. In the proposed system, a haptic device is used as the central mechanism for reverse engineering, shape modeling, real time mechanical property analysis, machining tool path planning and coordinate measuring machine (CMM) tolerance inspection path planning. With all these features in a single haptic system, it is possible to construct a three dimensional part by either haptic shape modeling or reverse engineering, then performing real-time mechanical property analysis in which the stiffness of a part can be felt and intuitively evaluated by the user, or generating collision free cutter tool path and CMM tolerance inspection path. Due to the force feed back in all of the above activities, the product development process is more intuitive, efficient and user-friendly. A prototype system has been developed to demonstrate the proposed capabilities.