A university fund for Article Processing Charges - experiences from Lund University

Presentation at the Nordic Perspectives on Open Access and Open Science seminar, Helsinki, October 15, 2013

Improving the competitiveness of electrolytic Zinc process by chemical reaction engineering approach

This doctoral thesis describes the development work performed on the leachand purification sections in the electrolytic zinc plant in Kokkola to increase the efficiency in these two stages, and thus the competitiveness of the plant. Since metallic zinc is a typical bulk product, the improvement of the competitiveness of a plant was mostly an issue of decreasing unit costs. The problems in the leaching were low recovery of valuable metals from raw materials, and that the available technology offered complicated and expensive processes to overcome this problem. In the purification, the main problem was consumption of zinc powder - up to four to six times the stoichiometric demand. This reduced the capacity of the plant as this zinc is re-circulated through the electrolysis, which is the absolute bottleneck in a zinc plant. Low selectivity gave low-grade and low-value precipitates for further processing to metallic copper, cadmium, cobalt and nickel. Knowledge of the underlying chemistry was poor and process interruptions causing losses of zinc production were frequent. Studies on leaching comprised the kinetics of ferrite leaching and jarosite precipitation, as well as the stability of jarosite in acidic plant solutions. A breakthrough came with the finding that jarosite could precipitate under conditions where ferrite would leach satisfactorily. Based on this discovery, a one-step process for the treatment of ferrite was developed. In the plant, the new process almost doubled the recovery of zinc from ferrite in the same equipment as the two-step jarosite process was operated in at that time. In a later expansion of the plant, investment savings were substantial compared to other technologies available. In the solution purification, the key finding was that Co, Ni, and Cu formed specific arsenides in the “hot arsenic zinc dust” step. This was utilized for the development of a three-step purification stage based on fluidized bed technology in all three steps, i.e. removal of Cu, Co and Cd. Both precipitation rates and selectivity increased, which strongly decreased the zinc powder consumption through a substantially suppressed hydrogen gas evolution. Better selectivity improved the value of the precipitates: cadmium, which caused environmental problems in the copper smelter, was reduced from 1-3% reported normally down to 0.05 %, and a cobalt cake with 15 % Co was easily produced in laboratory experiments in the cobalt removal. The zinc powder consumption in the plant for a solution containing Cu, Co, Ni and Cd (1000, 25, 30 and 350 mg/l, respectively), was around 1.8 g/l; i.e. only 1.4 times the stoichiometric demand – or, about 60% saving in powder consumption. Two processes for direct leaching of the concentrate under atmospheric conditions were developed, one of which was implemented in the Kokkola zinc plant. Compared to the existing pressure leach technology, savings were obtained mostly in investment. The scientific basis for the most important processes and process improvements is given in the doctoral thesis. This includes mathematical modeling and thermodynamic evaluation of experimental results and hypotheses developed. Five of the processes developed in this research and development program were implemented in the plant and are still operated. Even though these processes were developed with the focus on the plant in Kokkola, they can also be implemented at low cost in most of the zinc plants globally, and have thus a great significance in the development of the electrolytic zinc process in general.

Reframing the relationship between service design and operations: a service engineering approach

The significance of services as business and human activities has increased dramatically throughout the world in the last three decades. Becoming a more and more competitive and efficient service provider while still being able to provide unique value opportunities for customers requires new knowledge and ideas. Part of this knowledge is created and utilized in daily activities in every service organization, but not all of it, and therefore an emerging phenomenon in the service context is information awareness. Terms like big data and Internet of things are not only modern buzz-words but they are also describing urgent requirements for a new type of competences and solutions. When the amount of information increases and the systems processing information become more efficient and intelligent, it is the human understanding and objectives that may get separated from the automated processes and technological innovations. This is an important challenge and the core driver for this dissertation: What kind of information is created, possessed and utilized in the service context, and even more importantly, what information exists but is not acknowledged or used? In this dissertation the focus is on the relationship between service design and service operations. Reframing this relationship refers to viewing the service system from the architectural perspective. The selected perspective allows analysing the relationship between design activities and operational activities as an information system while maintaining the tight connection to existing service research contributions and approaches. This type of an innovative approach is supported by research methodology that relies on design science theory. The methodological process supports the construction of a new design artifact based on existing theoretical knowledge, creation of new innovations and testing the design artifact components in real service contexts. The relationship between design and operations is analysed in the health care and social care service systems. The existing contributions in service research tend to abstract services and service systems as value creation, working or interactive systems. This dissertation adds an important information processing system perspective to the research. The main contribution focuses on the following argument: Only part of the service information system is automated and computerized, whereas a significant part of information processing is embedded in human activities, communication and ad-hoc reactions. The results indicate that the relationship between service design and service operations is more complex and dynamic than the existing scientific and managerial models tend to view it. Both activities create, utilize, mix and share information, making service information management a necessary but relatively unknown managerial task. On the architectural level, service system -specific elements seem to disappear, but access to more general information elements and processes can be found. While this dissertation focuses on conceptual-level design artifact construction, the results provide also very practical implications for service providers. Personal, visual and hidden activities of service, and more importantly all changes that take place in any service system have also an information dimension. Making this information dimension visual and prioritizing the processed information based on service dimensions is likely to provide new opportunities to increase activities and provide a new type of service potential for customers.

Customer knowledge processing in maintenance business: case study

The purpose of the study is to examine and increase knowledge on customer knowledge processing in B2B context from sales perspective. Further objectives include identifying possible inhibiting and enabling factors in each phase of the process. The theoretical framework is based on customer knowledge management literature. The study is a qualitative study, in which the research method utilized is a case study. The empirical part was implemented in a case company by conducting in-depth interviews with the company’s value-selling champions located internationally. Context was maintenance business. Altogether 17 interviews were conducted. The empirical findings indicate that customer knowledge processing has not been clearly defined within the maintenance business line. Main inhibiting factors in acquiring customer knowledge are lack of time and vast amount of customer knowledge received. Enabling factors recognized are good customer relationships and sales representatives’ communication skills. Internal dissemination of knowledge is mainly inhibited by lack of time and restrictions in customer relationship management systems. Enabling factors are composition of the sales team and updated customer knowledge. Inhibiting utilization is lack of goals to utilize the customer knowledge and a low quality of the knowledge. Moreover, customer knowledge is not systematically updated nor analysed. Management of customer knowledge is based on the CRM system. As implications of the study, it is suggested for the case company to define customer knowledge processing in order to support maintenance business process.

Local Features in Image and Video Processing - Object Class Matching and Video Shot Detection

The usage of digital content, such as video clips and images, has increased dramatically during the last decade. Local image features have been applied increasingly in various image and video retrieval applications. This thesis evaluates local features and applies them to image and video processing tasks. The results of the study show that 1) the performance of different local feature detector and descriptor methods vary significantly in object class matching, 2) local features can be applied in image alignment with superior results against the state-of-the-art, 3) the local feature based shot boundary detection method produces promising results, and 4) the local feature based hierarchical video summarization method shows promising new new research direction. In conclusion, this thesis presents the local features as a powerful tool in many applications and the imminent future work should concentrate on improving the quality of the local features.

Scientific creativity and diversity of physical work environment: framework development

The aim of this research was to develop a framework to analyze how physical environment influences scientific creativity. Due to the relative novelty of this topic, there is still a gap in the unified method to study connection between physical environment and creativity. Therefore, in order to study this issue deeply, the qualitative method was used (interviews and qualitative questionnaire). Scientists (PhD students and senior researchers) of Graduate School of Management were interviewed to build the model and one expert interview was conducted to assess its validity. The model highlights several dimensions via which physical environment can influence scientific creativity: Comfort, Instruments and Diversity. Comfort and Instruments are considered to be related mostly to productivity, an initial requirement for creativity, while Diversity is the factor responsible for supporting all the stages of scientific creative process. Thus, creative physical environment is not one place by its nature, but an aggregative phenomenon. Due to two levels of analysis, the model is named the two-level model of creative physical environment.

A distributed, cloud-ready, digital content processing and transformation platform and a specific use case

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Targeted Annotation of Scientific Literature and Data Resources in Invenio Digital Libraries

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Big Data Processing in the Cloud: a Hydra/Sufia Experience

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Self-deposit, discovery, and delivery of scientific GIS datasets using GeoHydra

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Geo-enabling repositories - techniques, tools, and challenges

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Biomedical Event Extraction with Machine Learning

Biomedical natural language processing (BioNLP) is a subfield of natural language processing, an area of computational linguistics concerned with developing programs that work with natural language: written texts and speech. Biomedical relation extraction concerns the detection of semantic relations such as protein-protein interactions (PPI) from scientific texts. The aim is to enhance information retrieval by detecting relations between concepts, not just individual concepts as with a keyword search. In recent years, events have been proposed as a more detailed alternative for simple pairwise PPI relations. Events provide a systematic, structural representation for annotating the content of natural language texts. Events are characterized by annotated trigger words, directed and typed arguments and the ability to nest other events. For example, the sentence “Protein A causes protein B to bind protein C” can be annotated with the nested event structure CAUSE(A, BIND(B, C)). Converted to such formal representations, the information of natural language texts can be used by computational applications. Biomedical event annotations were introduced by the BioInfer and GENIA corpora, and event extraction was popularized by the BioNLP'09 Shared Task on Event Extraction. In this thesis we present a method for automated event extraction, implemented as the Turku Event Extraction System (TEES). A unified graph format is defined for representing event annotations and the problem of extracting complex event structures is decomposed into a number of independent classification tasks. These classification tasks are solved using SVM and RLS classifiers, utilizing rich feature representations built from full dependency parsing. Building on earlier work on pairwise relation extraction and using a generalized graph representation, the resulting TEES system is capable of detecting binary relations as well as complex event structures. We show that this event extraction system has good performance, reaching the first place in the BioNLP'09 Shared Task on Event Extraction. Subsequently, TEES has achieved several first ranks in the BioNLP'11 and BioNLP'13 Shared Tasks, as well as shown competitive performance in the binary relation Drug-Drug Interaction Extraction 2011 and 2013 shared tasks. The Turku Event Extraction System is published as a freely available open-source project, documenting the research in detail as well as making the method available for practical applications. In particular, in this thesis we describe the application of the event extraction method to PubMed-scale text mining, showing how the developed approach not only shows good performance, but is generalizable and applicable to large-scale real-world text mining projects. Finally, we discuss related literature, summarize the contributions of the work and present some thoughts on future directions for biomedical event extraction. This thesis includes and builds on six original research publications. The first of these introduces the analysis of dependency parses that leads to development of TEES. The entries in the three BioNLP Shared Tasks, as well as in the DDIExtraction 2011 task are covered in four publications, and the sixth one demonstrates the application of the system to PubMed-scale text mining.