Key performance indicators for innovation implementation : perception vs. actual usage

This paper aimed to explore the proportion associated with the perceived importance and the actual use of performance indicators from manufacturing and non manufacturing industries. The sample was 86 small and medium sized-organizations in Thailand. The perceived importance and the actual use of financial and non financial indicators were found to be significantly related among manufacturing and non manufacturing industries. KPI 3, 9, and 12 (i.e. sales and sales growth; quality of products and /or services; and process time) were perceived the most importance among manufacturing managers (85.3%, 79.4% and 76.5% respectively). While KPI 6, 9, and 12 (i.e. customer satisfaction, quality of products and /or services; and process time) were perceived the most importance among non manufacturing managers (84.8%, 93.5%, and 84.8% respectively). Interestingly, the most used KPIs for manufacturing were sales and sales growth (64.7%); profit margins (61.8%); and customer satisfaction (84.8) while non manufacturing used quality products/services (60.9%); sales and sales growth (54.3%) and employee development (54.3%) respectively. Limitation and implication were also discussed.

Yield-factor volatility models

The term structure of interest rates is often summarized using a handful of yield factors that capture shifts in the shape of the yield curve. In this paper, we develop a comprehensive model for volatility dynamics in the level, slope, and curvature of the yield curve that simultaneously includes level and GARCH effects along with regime shifts. We show that the level of the short rate is useful in modeling the volatility of the three yield factors and that there are significant GARCH effects present even after including a level effect. Further, we find that allowing for regime shifts in the factor volatilities dramatically improves the model’s fit and strengthens the level effect. We also show that a regime-switching model with level and GARCH effects provides the best out-of-sample forecasting performance of yield volatility. We argue that the auxiliary models often used to estimate term structure models with simulation-based estimation techniques should be consistent with the main features of the yield curve that are identified by our model.

Reliability analysis of transform-based stereo matching techniques, and a new matching constraint

Stereo vision is a method of depth perception, in which depth information is inferred from two (or more) images of a scene, taken from different perspectives. Practical applications for stereo vision include aerial photogrammetry, autonomous vehicle guidance, robotics and industrial automation. The initial motivation behind this work was to produce a stereo vision sensor for mining automation applications. For such applications, the input stereo images would consist of close range scenes of rocks. A fundamental problem faced by matching algorithms is the matching or correspondence problem. This problem involves locating corresponding points or features in two images. For this application, speed, reliability, and the ability to produce a dense depth map are of foremost importance. This work implemented a number of areabased matching algorithms to assess their suitability for this application. Area-based techniques were investigated because of their potential to yield dense depth maps, their amenability to fast hardware implementation, and their suitability to textured scenes such as rocks. In addition, two non-parametric transforms, the rank and census, were also compared. Both the rank and the census transforms were found to result in improved reliability of matching in the presence of radiometric distortion - significant since radiometric distortion is a problem which commonly arises in practice. In addition, they have low computational complexity, making them amenable to fast hardware implementation. Therefore, it was decided that matching algorithms using these transforms would be the subject of the remainder of the thesis. An analytic expression for the process of matching using the rank transform was derived from first principles. This work resulted in a number of important contributions. Firstly, the derivation process resulted in one constraint which must be satisfied for a correct match. This was termed the rank constraint. The theoretical derivation of this constraint is in contrast to the existing matching constraints which have little theoretical basis. Experimental work with actual and contrived stereo pairs has shown that the new constraint is capable of resolving ambiguous matches, thereby improving match reliability. Secondly, a novel matching algorithm incorporating the rank constraint has been proposed. This algorithm was tested using a number of stereo pairs. In all cases, the modified algorithm consistently resulted in an increased proportion of correct matches. Finally, the rank constraint was used to devise a new method for identifying regions of an image where the rank transform, and hence matching, are more susceptible to noise. The rank constraint was also incorporated into a new hybrid matching algorithm, where it was combined a number of other ideas. These included the use of an image pyramid for match prediction, and a method of edge localisation to improve match accuracy in the vicinity of edges. Experimental results obtained from the new algorithm showed that the algorithm is able to remove a large proportion of invalid matches, and improve match accuracy.

Cultivar-specific effects of pathogen testing on storage root yield of sweet potato, Ipomoea batatas (L.) Lam.

The accumulation and perpetuation of viral pathogens over generations of clonal propagation in crop species such as sweet potato, Ipomoea batatas,inevitably result in a reduction in crop yield and quality. This study was conducted at Bundaberg, Australia to compare the productivity of field-derived and pathogen-tested (PT)clones of 14 sweet potato cultivars and the yield benefits of using healthy planting materials. The field-derived clonal materials were exposed to the endemic viruses, while the PT clones were subjected to thermotherapy and meristem-tip culture to eliminate viral pathogens. The plants were indexed for viruses using nitrocellulose membrane-enzyme-linked immunosorbent assay and graft-inoculations onto Ipomoea setosa. A net benefit of 38% in storage root yield was realised from using PT materials in this study.Conversely, in a similar study previously conducted at Kerevat, Papua New Guinea (PNG), a net deficit of 36% was realised. This reinforced our finding that the response to pathogen testing was cultivar dependent and that the PNG cultivars in these studies generally exhibited increased tolerance to the endemic viruses present at the respective trial sites as manifested in their lack of response from the use of PT clones. They may be useful sources for future resistance breeding efforts. Nonetheless, the potential economic gain from using PT stocks necessitates the use of pathogen testing on virus-susceptible commercial cultivars.

Manufacturing Yield Improvement by Clustering

Dealing with product yield and quality in manufacturing industries is getting more difficult due to the increasing volume and complexity of data and quicker time to market expectations. Data mining offers tools for quick discovery of relationships, patterns and knowledge in large databases. Growing self-organizing map (GSOM) is established as an efficient unsupervised datamining algorithm. In this study some modifications to the original GSOM are proposed for manufacturing yield improvement by clustering. These modifications include introduction of a clustering quality measure to evaluate the performance of the programme in separating good and faulty products and a filtering index to reduce noise from the dataset. Results show that the proposed method is able to effectively differentiate good and faulty products. It will help engineers construct the knowledge base to predict product quality automatically from collected data and provide insights for yield improvement.