Effect of Hardwood Sawmill Edging and Trimming Practices on Furniture Part Production
In a recent edging and trimming study at three hardwood sawmills, it was observed that the lumber volume produced was approximately 10 percent less than would be necessary to make the most valuable lumber. Furthermore, the excess portion of wood that was removed from the edging and trimming process contained a large percentage of clear wood. In light of rising costs and increasing environmental concerns, the option of producing furniture parts from unedged and untrimmed boards is explored. This research investigates the potential furniture part yields from unedged and untrimmed boards compared to both optimal and actual edging and trimming practices. The resulting volume of cuttings from unedged and untrimmed boards was found to be 25 percent higher than from the actual edged and trimmed lumber produced at the mills.
An analysis of the North American market for wood scanners
Innovativ Vision AB develops and delivers quality and production control systems for the woodworking industry. North America is emerging as one of the most important markets for Innovativ Vision AB and their scanner WoodEye. Since 2001 Innovativ Vision AB has an office in the USA for customer service and support. In 2004 they also established a local sales and distributions office in USA. Innovativ Vision AB is in the process of developing WoodEye's new software Edger, Planer and NHLA. A market analysis is necessary in order to establish suitable plans of actions for further launching of the new software in the North American sawmill industry market. 
 
The objects of this thesis are: 1/ To establish which segment areas are potential markets for Innovativ Vision AB. 2/ Investigate which aspects of what is being offered to the customer from scanner optimizing manufacturers are most valued by the customers and how these aspects affect the feeling of trust and commitment between the manufacturer and their customers. The chosen associations for visits were restricted to the east coast, while associations in other parts of North America were contacted by telephone and mail. 
 
The outcome of this thesis provides an overview of, and an introduction to, the North American market for Innovativ Vision AB. Nine semi structured qualitative interviews were performed in North America, five with associations and four with sawmills. Other than these, an additional interview was performed with a Swedish sawmill prior to the trip, providing a total of ten interviews as a basis for this market analysis. 
 
The main conclusions drawn are that there are no investments being made by sawmills due to the current downturn in the housing sector. However, there is a huge demand for an optimizer that grades southern yellow pine accurately. A few competitors in Canada represent a large proportion of market share and that bad service can be disastrous for an optimizer manufacturer's reputation. When asking the associations about optimizers fitting the description of Innovativ Vision AB's new software, Edger, Planer and NHLA, the most common reaction from the respondents was that they were not experts on that area and could not give a detailed answer. A natural continuation would be to make a more thorough analysis of competitors and potential customers in a restricted geographic area.
Research on Fracture Recognition in Well Logging Images: Adversarial Learning with Attention
Semantic recognition of fractures in well logging images is vital for engineers to implement oil and gas exploration. An essential approach to accomplishing the object is to adopt deep learning based on convolutional neural networks. However, due to the lack of annotated labels in well logging images, it is scarcely available to directly train the semantic segmentation network. In this paper, we explore a domain shift model attempting to achieve domain adaptation from one annotated dataset to our target well logging images. This model's core is to utilize adversarial learning, including generator and discriminator, which can prompt the model to generate fracture segmentation similar to the source domain in the target domain. For enhancing the domain adaptive model further, an attention module is introduced, which can suppress redundant noise in semantic segmentation results. We demonstrate that our proposed model performs well by extensive tests and ablation experiments in the ultrasonic well logging images.