Anticipating user experience with a desired product : the AUX Framework

Positive user experience (UX) has become a key factor in designing interactive products. It acts as a differentiator which can determine a product’s success on the mature market. However, current UX frameworks and methods do not fully support the early stages of product design and development. During these phases, assessment of UX is challenging as no actual user-product interaction can be tested. This qualitative study investigated anticipated user experience (AUX) to address this problem. Using the co-discovery method, participants were asked to imagine a desired product, anticipate experiences with it, and discuss their views with another participant. Fourteen sub-categories emerged from the data, and relationships among them were defined through co-occurrence analysis. These data formed the basis of the AUX framework which consists of two networks which elucidate 1) how users imagine a desired product and 2) how they anticipate positive experiences with that product. Through this AUX framework, important factors in the process of imagining future products and experiences were learnt, including the way in which these factors interrelate. Focusing on and exploring each component of the two networks in the framework will allow designers to obtain a deeper understanding of the required pragmatic and hedonic qualities of product, intended uses of product, user characteristics, potential contexts of experience, and anticipated emotions embedded within the experience. This understanding, in turn, will help designers to better foresee users’ underlying needs and to focus on the most important aspects of their positive experience. Therefore, the use of the AUX framework in the early stages of product development will contribute to the design for pleasurable UX.

A parallel cooperative co-evolutionary genetic algorithm for the composite SaaS placement problem in Cloud computing

A composite SaaS (Software as a Service) is a software that is comprised of several software components and data components. The composite SaaS placement problem is to determine where each of the components should be deployed in a cloud computing environment such that the performance of the composite SaaS is optimal. From the computational point of view, the composite SaaS placement problem is a large-scale combinatorial optimization problem. Thus, an Iterative Cooperative Co-evolutionary Genetic Algorithm (ICCGA) was proposed. The ICCGA can find reasonable quality of solutions. However, its computation time is noticeably slow. Aiming at improving the computation time, we propose an unsynchronized Parallel Cooperative Co-evolutionary Genetic Algorithm (PCCGA) in this paper. Experimental results have shown that the PCCGA not only has quicker computation time, but also generates better quality of solutions than the ICCGA.

Learning domain-specific sentiment lexicons for predicting product sales

Generic sentiment lexicons have been widely used for sentiment analysis these days. However, manually constructing sentiment lexicons is very time-consuming and it may not be feasible for certain application domains where annotation expertise is not available. One contribution of this paper is the development of a statistical learning based computational method for the automatic construction of domain-specific sentiment lexicons to enhance cross-domain sentiment analysis. Our initial experiments show that the proposed methodology can automatically generate domain-specific sentiment lexicons which contribute to improve the effectiveness of opinion retrieval at the document level. Another contribution of our work is that we show the feasibility of applying the sentiment metric derived based on the automatically constructed sentiment lexicons to predict product sales of certain product categories. Our research contributes to the development of more effective sentiment analysis system to extract business intelligence from numerous opinionated expressions posted to the Web

Automated support for versioning compliance checking between workflow management and product lifecycle management (in Chinese)

With the development of enterprise informatisation, Product Lifecycle Management (PLM) systems have been widely deployed and applied in enterprises. This paper analyzes the requirement that conducting version operations on business objects as specified in process models should be compliant with the versioning policies imposed by product lifecycles. This leads to the introduction of the concept of versioning compliance, and the approach of compliance checking that we proposed in our earlier work, which comprises both syntactical compatibility and behavioural compatibility checking. The paper then focuses on the tool implementation for providing automated support to the versioning compliance checking. An empirical evaluation of the tool was also performed with industrial partners using the well-known questionnaire-based method. The evaluation and feedback from practitioners further evidence the practical significance of this research question in the PLM field and demonstrate that the proposed solution with its automated tool support possesses a high application potential.

Increasing loyalty to breastfeeding : investigating a product development strategy

This paper demonstrates how social marketing insights were used to influence women’s loyalty to breastfeeding. The paper reports on a social marketing campaign undertaken by the Australian Breastfeeding Association and a government health department, which used a product development strategy in order to increase breastfeeding loyalty. Seeking new approaches to support breastfeeding behaviors is critical and timely, because while initiation rates of breastfeeding are high in developed countries such as the UK, Australia, Canada, and the USA, duration rates are significantly lower. Results indicate that a product focused strategy influences pregnant women’s loyalty to exclusively breastfeeding.

Interactive product browsing and configuration using remote augmented reality sales services

Real-time remote sales assistance is an underdeveloped component of online sales services. Solutions involving web page text chat, telephony and video support prove problematic when seeking to remotely guide customers in their sales processes, especially with configurations of physically complex artefacts. Recently, there has been great interest in the application of virtual worlds and augmented reality to create synthetic environments for remote sales of physical artefacts. However, there is a lack of analysis and development of appropriate software services to support these processes. We extend our previous work with the detailed design of configuration context services to support the management of an interactive sales session using augmented reality. We detail the context and configuration services required, presenting a novel data service streaming configuration information to the vendor for business analytics. We expect that a fully implemented configuration management service, based on our design, will improve the remote sales experience for both customers and vendors alike via analysis of the streamed information.

A simulated annealing algorithm for energy efficient virtual machine placement

Improving energy efficiency has become increasingly important in data centers in recent years to reduce the rapidly growing tremendous amounts of electricity consumption. The power dissipation of the physical servers is the root cause of power usage of other systems, such as cooling systems. Many efforts have been made to make data centers more energy efficient. One of them is to minimize the total power consumption of these servers in a data center through virtual machine consolidation, which is implemented by virtual machine placement. The placement problem is often modeled as a bin packing problem. Due to the NP-hard nature of the problem, heuristic solutions such as First Fit and Best Fit algorithms have been often used and have generally good results. However, their performance leaves room for further improvement. In this paper we propose a Simulated Annealing based algorithm, which aims at further improvement from any feasible placement. This is the first published attempt of using SA to solve the VM placement problem to optimize the power consumption. Experimental results show that this SA algorithm can generate better results, saving up to 25 percentage more energy than First Fit Decreasing in an acceptable time frame.

Energy-efficient virtual machine placement in data centers by genetic algorithm

Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches to the virtual machine placement problem consider the energy consumption by physical machines in a data center only, but do not consider the energy consumption in communication network in the data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement in order to make the data center more energy-efficient. In this paper, we propose a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both the servers and the communication network in the data center. Experimental results show that the genetic algorithm performs well when tackling test problems of different kinds, and scales up well when the problem size increases.

A novel cyclization product from the polyphosphoric acid catalyzed addition of propanal to limonene

The polyphosphoric acid catalyzed addition of propanal to limonene yielded a novel bicyclic ether 2,2,6-trimethyl-4-ethyl-3-oxabicyclo[3.3.1]non-6-ene (I). The yield of (I) was significantly increased by carrying out the reaction under nitrogen rather than in air.

A framework for life cycle cost estimation of a product family at the early stage of product development

A cost estimation method is required to estimate the life cycle cost of a product family at the early stage of product development in order to evaluate the product family design. There are difficulties with existing cost estimation techniques in estimating the life cycle cost for a product family at the early stage of product development. This paper proposes a framework that combines a knowledge based system and an activity based costing techniques in estimating the life cycle cost of a product family at the early stage of product development. The inputs of the framework are the product family structure and its sub function. The output of the framework is the life cycle cost of a product family that consists of all costs at each product family level and the costs of each product life cycle stage. The proposed framework provides a life cycle cost estimation tool for a product family at the early stage of product development using high level information as its input. The framework makes it possible to estimate the life cycle cost of various product family that use any types of product structure. It provides detailed information related to the activity and resource costs of both parts and products that can assist the designer in analyzing the cost of the product family design. In addition, it can reduce the required amount of information and time to construct the cost estimation system.

A visual language for the collaborative visualization of integrated conceptual models in product development scenarios

In various industrial and scientific fields, conceptual models are derived from real world problem spaces to understand and communicate containing entities and coherencies. Abstracted models mirror the common understanding and information demand of engineers, who apply conceptual models for performing their daily tasks. However, most standardized models in Process Management, Product Lifecycle Management and Enterprise Resource Planning lack of a scientific foundation for their notation. In collaboration scenarios with stakeholders from several disciplines, tailored conceptual models complicate communication processes, as a common understanding is not shared or implemented in specific models. To support direct communication between experts from several disciplines, a visual language is developed which allows a common visualization of discipline-specific conceptual models. For visual discrimination and to overcome visual complexity issues, conceptual models are arranged in a three-dimensional space. The visual language introduced here follows and extends established principles of Visual Language science.

Bioreactor for blood product production

The feasibility of ex vivo blood production is limited by both biological and engineering challenges. From an engineering perspective, these challenges include the significant volumes required to generate even a single unit of a blood product, as well as the correspondingly high protein consumption required for such large volume cultures. Membrane bioreactors, such as hollow fiber bioreactors (HFBRs), enable cell densities approximately 100-fold greater than traditional culture systems and therefore may enable a significant reduction in culture working volumes. As cultured cells, and larger molecules, are retained within a fraction of the system volume, via a semipermeable membrane it may be possible to reduce protein consumption by limiting supplementation to only this fraction. Typically, HFBRs are complex perfusion systems having total volumes incompatible with bench scale screening and optimization of stem cell-based cultures. In this article we describe the use of a simplified HFBR system to assess the feasibility of this technology to produce blood products from umbilical cord blood-derived CD34+ hematopoietic stem progenitor cells (HSPCs). Unlike conventional HFBR systems used for protein manufacture, where cells are cultured in the extracapillary space, we have cultured cells in the intracapillary space, which is likely more compatible with the large-scale production of blood cell suspension cultures. Using this platform we direct HSPCs down the myeloid lineage, while targeting a 100-fold increase in cell density and the use of protein-free bulk medium. Our results demonstrate the potential of this system to deliver high cell densities, even in the absence of protein supplementation of the bulk medium.

Reduced expression of retinoblastoma gene product (pRB) and high expression of p53 are associated with poor prognosis in ovarian cancer

Paraffin sections (n = 168, 27 benign, 16 low malignant potential [LMP] and 125 malignant tumours) from epithelial ovarian tumours were evaluated immunohistochemically for expression of retinoblastoma gene product (pRB) and p53 protein, and the relationship among pRB, p53 and cyclin-dependent kinase inhibitor 2 (CDKN2) gene product p16INK4A (p16) was analysed, following our previous study of p16. Forty-one percent of the benign, 50% of the LMP and most (71%) of the malignant tumours showed high pRB expression. High expression of pRB (>50% pRB-positive cells) significantly correlated with non-mucinous histological subtypes. Reduced pRB expression, substage and residual disease were significant predictors for poor prognosis in stage I patients. All the benign and most of the LMP (81%) tumours were in either the p53-negative or low p53-positive category, but nearly half of the malignant tumours had high p53 expression. High p53 accumulation was found in non-mucinous, high grade and late stage tumours. For well-differentiated carcinomas, high p53 expression was a predictor of poor prognosis. However, even though high p53 expression was not associated with histological subtype, stage or the presence of residual disease, high p53 expression was not an independent predictor when all clinical parameters were combined. For all ovarian cancers, a close correlation was found between high p53 and high p16 expression. The relationship between the expression of pRB and p16 depended on tumour stage. In stage I tumours, high pRB was associated with low p16 reactivity. On the other hand, most advanced tumours showed both high pRB and high p16 reactivity. Int. J. Cancer 74:407–415, 1997. © 1997 Wiley-Liss, Inc.

Increased expression of cyclin-dependent kinase inhibitor 2 (CDKN2A) gene product P16INK4A in ovarian cancer is associated with progression and unfavourable prognosis

Paraffin sections from 190 epithelial ovarian tumours, including 159 malignant and 31 benign epithelial tumours, were analysed immunohistochemically for expression of cyclin-dependent kinase inhibitor 2 (CDKN2A) gene product p16INK4A (p16). Most benign tumours showed no p16 expression in the tumour cells, whereas only 11% of malignant cancers were p16 negative. A high proportion of p16-positive tumour cells was associated with advanced stage and grade, and with poor prognosis in cancer patients. For FIGO stage 1 tumours, a high proportion of p16-positive tumour cells was associated with poorer survival, suggesting that accumulation of p16 is an early event of ovarian tumorigenesis. In contrast to tumour cells, high expression of p16 in the surrounding stromal cells was not associated with the stage and grade, but was associated with longer survival. When all parameters were combined in multivariate analysis, high p16 expression in stromal cells was not an independent predictor for survival, indicating that low p16 expression in stromal cells is associated with other markers of tumour progression. High expression of p16 survival in the stromal cells of tumours from long-term survivors suggests that tumour growth is limited to some extent by factors associated with p16 expression in the matrix.