Kuali OLE: A Collaborative ILS Partnership

Presentation of Robert H. McDonald at the Library Network Days, October 22, 2014 in Helsinki. – Esitys Kirjastoverkkopäivillä 22.10.2014 Helsingissä

Evidencing and Sharing Value with Decision Making Models in an Industrial Maintenance Network

The objective of this thesis is to concretize the potential benefits that the industrial maintenance case network could achieve through using the value-based life-cycle model and the flexible asset management model. It is also inspected what factors prevent value creation and sharing in the maintenance contract practices of the case network. This thesis is a case study which utilizes modelling. Four scenarios were developed to demonstrate value creation in the future. The data was partly provided by the collaborating company, partly gathered from public financial statement information. The results indicate that value has been created through the past maintenance of the collaborating company’s rod mill and that profitability of the collaborating company has been mostly on satisfactory level during the past few years. Potential value might be created by increasing the share of proactive maintenance of the rod mill in the future. Profitability of the network could be improved in the future through flexible asset management operations. The main obstacle for value creation and sharing seems to be the lack of sufficient trust between the network members.

Biochemical adaptations of mammalian hibernation: exploring squirrels as a perspective model for naturally induced reversible insulin resistance

An important disease among human metabolic disorders is type 2 diabetes mellitus. This disorder involves multiple physiological defects that result from high blood glucose content and eventually lead to the onset of insulin resistance. The combination of insulin resistance, increased glucose production, and decreased insulin secretion creates a diabetic metabolic environment that leads to a lifetime of management. Appropriate models are critical for the success of research. As such, a unique model providing insight into the mechanisms of reversible insulin resistance is mammalian hibernation. Hibernators, such as ground squirrels and bats, are excellent examples of animals exhibiting reversible insulin resistance, for which a rapid increase in body weight is required prior to entry into dormancy. Hibernator studies have shown differential regulation of specific molecular pathways involved in reversible resistance to insulin. The present review focuses on this growing area of research and the molecular mechanisms that regulate glucose homeostasis, and explores the roles of the Akt signaling pathway during hibernation. Here, we propose a link between hibernation, a well-documented response to periods of environmental stress, and reversible insulin resistance, potentially facilitated by key alterations in the Akt signaling network, PPAR-γ/PGC-1α regulation, and non-coding RNA expression. Coincidentally, many of the same pathways are frequently found to be dysregulated during insulin resistance in human type 2 diabetes. Hence, the molecular networks that may regulate reversible insulin resistance in hibernating mammals represent a novel approach by providing insight into medical treatment of insulin resistance in humans.

Artificial neural network models for predicting 1-year mortality in elderly patients with intertrochanteric fractures in China

The mortality rate of older patients with intertrochanteric fractures has been increasing with the aging of populations in China. The purpose of this study was: 1) to develop an artificial neural network (ANN) using clinical information to predict the 1-year mortality of elderly patients with intertrochanteric fractures, and 2) to compare the ANN's predictive ability with that of logistic regression models. The ANN model was tested against actual outcomes of an intertrochanteric femoral fracture database in China. The ANN model was generated with eight clinical inputs and a single output. ANN's performance was compared with a logistic regression model created with the same inputs in terms of accuracy, sensitivity, specificity, and discriminability. The study population was composed of 2150 patients (679 males and 1471 females): 1432 in the training group and 718 new patients in the testing group. The ANN model that had eight neurons in the hidden layer had the highest accuracies among the four ANN models: 92.46 and 85.79% in both training and testing datasets, respectively. The areas under the receiver operating characteristic curves of the automatically selected ANN model for both datasets were 0.901 (95%CI=0.814-0.988) and 0.869 (95%CI=0.748-0.990), higher than the 0.745 (95%CI=0.612-0.879) and 0.728 (95%CI=0.595-0.862) of the logistic regression model. The ANN model can be used for predicting 1-year mortality in elderly patients with intertrochanteric fractures. It outperformed a logistic regression on multiple performance measures when given the same variables.

Transduction motif analysis of gastric cancer based on a human signaling network

To investigate signal regulation models of gastric cancer, databases and literature were used to construct the signaling network in humans. Topological characteristics of the network were analyzed by CytoScape. After marking gastric cancer-related genes extracted from the CancerResource, GeneRIF, and COSMIC databases, the FANMOD software was used for the mining of gastric cancer-related motifs in a network with three vertices. The significant motif difference method was adopted to identify significantly different motifs in the normal and cancer states. Finally, we conducted a series of analyses of the significantly different motifs, including gene ontology, function annotation of genes, and model classification. A human signaling network was constructed, with 1643 nodes and 5089 regulating interactions. The network was configured to have the characteristics of other biological networks. There were 57,942 motifs marked with gastric cancer-related genes out of a total of 69,492 motifs, and 264 motifs were selected as significantly different motifs by calculating the significant motif difference (SMD) scores. Genes in significantly different motifs were mainly enriched in functions associated with cancer genesis, such as regulation of cell death, amino acid phosphorylation of proteins, and intracellular signaling cascades. The top five significantly different motifs were mainly cascade and positive feedback types. Almost all genes in the five motifs were cancer related, including EPOR,MAPK14, BCL2L1, KRT18,PTPN6, CASP3, TGFBR2,AR, and CASP7. The development of cancer might be curbed by inhibiting signal transductions upstream and downstream of the selected motifs.

HYBRID ARTIFICIAL NEURAL NETWORK APPLIEDTO MODELING SCFE OF BASIL AND ROSEMARY OILS

This work presents the results of a Hybrid Neural Network (HNN) technique as applied to modeling SCFE curves obtained from two Brazilian vegetable matrices. A series Hybrid Neural Network was employed to estimate the parameters of the phenomenological model. A small set of SCFE data of each vegetable was used to generate an extended data set, sufficient to train the network. Afterwards, other sets of experimental data, not used in the network training, were used to validate the present approach. The series HNN correlates well the experimental data and it is shown that the predictions accomplished with this technique may be promising for SCFE purposes.

Socially shared metacognitive regulation during collaborative learning processes in student dyads and small groups

Traditionally metacognition has been theorised, methodologically studied and empirically tested from the standpoint mainly of individuals and their learning contexts. In this dissertation the emergence of metacognition is analysed more broadly. The aim of the dissertation was to explore socially shared metacognitive regulation (SSMR) as part of collaborative learning processes taking place in student dyads and small learning groups. The specific aims were to extend the concept of individual metacognition to SSMR, to develop methods to capture and analyse SSMR and to validate the usefulness of the concept of SSMR in two different learning contexts; in face-to-face student dyads solving mathematical word problems and also in small groups taking part in inquiry-based science learning in an asynchronous computer-supported collaborative learning (CSCL) environment. This dissertation is comprised of four studies. In Study I, the main aim was to explore if and how metacognition emerges during problem solving in student dyads and then to develop a method for analysing the social level of awareness, monitoring, and regulatory processes emerging during the problem solving. Two dyads comprised of 10-year-old students who were high-achieving especially in mathematical word problem solving and reading comprehension were involved in the study. An in-depth case analysis was conducted. Data consisted of over 16 (30–45 minutes) videotaped and transcribed face-to-face sessions. The dyads solved altogether 151 mathematical word problems of different difficulty levels in a game-format learning environment. The interaction flowchart was used in the analysis to uncover socially shared metacognition. Interviews (also stimulated recall interviews) were conducted in order to obtain further information about socially shared metacognition. The findings showed the emergence of metacognition in a collaborative learning context in a way that cannot solely be explained by individual conception. The concept of socially-shared metacognition (SSMR) was proposed. The results highlighted the emergence of socially shared metacognition specifically in problems where dyads encountered challenges. Small verbal and nonverbal signals between students also triggered the emergence of socially shared metacognition. Additionally, one dyad implemented a system whereby they shared metacognitive regulation based on their strengths in learning. Overall, the findings suggested that in order to discover patterns of socially shared metacognition, it is important to investigate metacognition over time. However, it was concluded that more research on socially shared metacognition, from larger data sets, is needed. These findings formed the basis of the second study. In Study II, the specific aim was to investigate whether socially shared metacognition can be reliably identified from a large dataset of collaborative face-to-face mathematical word problem solving sessions by student dyads. We specifically examined different difficulty levels of tasks as well as the function and focus of socially shared metacognition. Furthermore, the presence of observable metacognitive experiences at the beginning of socially shared metacognition was explored. Four dyads participated in the study. Each dyad was comprised of high-achieving 10-year-old students, ranked in the top 11% of their fourth grade peers (n=393). Dyads were from the same data set as in Study I. The dyads worked face-to-face in a computer-supported, game-format learning environment. Problem-solving processes for 251 tasks at three difficulty levels taking place during 56 (30–45 minutes) lessons were video-taped and analysed. Baseline data for this study were 14 675 turns of transcribed verbal and nonverbal behaviours observed in four study dyads. The micro-level analysis illustrated how participants moved between different channels of communication (individual and interpersonal). The unit of analysis was a set of turns, referred to as an ‘episode’. The results indicated that socially shared metacognition and its function and focus, as well as the appearance of metacognitive experiences can be defined in a reliable way from a larger data set by independent coders. A comparison of the different difficulty levels of the problems suggested that in order to trigger socially shared metacognition in small groups, the problems should be more difficult, as opposed to moderately difficult or easy. Although socially shared metacognition was found in collaborative face-to-face problem solving among high-achieving student dyads, more research is needed in different contexts. This consideration created the basis of the research on socially shared metacognition in Studies III and IV. In Study III, the aim was to expand the research on SSMR from face-to-face mathematical problem solving in student dyads to inquiry-based science learning among small groups in an asynchronous computer-supported collaborative learning (CSCL) environment. The specific aims were to investigate SSMR’s evolvement and functions in a CSCL environment and to explore how SSMR emerges at different phases of the inquiry process. Finally, individual student participation in SSMR during the process was studied. An in-depth explanatory case study of one small group of four girls aged 12 years was carried out. The girls attended a class that has an entrance examination and conducts a language-enriched curriculum. The small group solved complex science problems in an asynchronous CSCL environment, participating in research-like processes of inquiry during 22 lessons (á 45–minute). Students’ network discussion were recorded in written notes (N=640) which were used as study data. A set of notes, referred to here as a ‘thread’, was used as the unit of analysis. The inter-coder agreement was regarded as substantial. The results indicated that SSMR emerges in a small group’s asynchronous CSCL inquiry process in the science domain. Hence, the results of Study III were in line with the previous Study I and Study II and revealed that metacognition cannot be reduced to the individual level alone. The findings also confirm that SSMR should be examined as a process, since SSMR can evolve during different phases and that different SSMR threads overlapped and intertwined. Although the classification of SSMR’s functions was applicable in the context of CSCL in a small group, the dominant function was different in the asynchronous CSCL inquiry in the small group in a science activity than in mathematical word problem solving among student dyads (Study II). Further, the use of different analytical methods provided complementary findings about students’ participation in SSMR. The findings suggest that it is not enough to code just a single written note or simply to examine who has the largest number of notes in the SSMR thread but also to examine the connections between the notes. As the findings of the present study are based on an in-depth analysis of a single small group, further cases were examined in Study IV, as well as looking at the SSMR’s focus, which was also studied in a face-to-face context. In Study IV, the general aim was to investigate the emergence of SSMR with a larger data set from an asynchronous CSCL inquiry process in small student groups carrying out science activities. The specific aims were to study the emergence of SSMR in the different phases of the process, students’ participation in SSMR, and the relation of SSMR’s focus to the quality of outcomes, which was not explored in previous studies. The participants were 12-year-old students from the same class as in Study III. Five small groups consisting of four students and one of five students (N=25) were involved in the study. The small groups solved ill-defined science problems in an asynchronous CSCL environment, participating in research-like processes of inquiry over a total period of 22 hours. Written notes (N=4088) detailed the network discussions of the small groups and these constituted the study data. With these notes, SSMR threads were explored. As in Study III, the thread was used as the unit of analysis. In total, 332 notes were classified as forming 41 SSMR threads. Inter-coder agreement was assessed by three coders in the different phases of the analysis and found to be reliable. Multiple methods of analysis were used. Results showed that SSMR emerged in all the asynchronous CSCL inquiry processes in the small groups. However, the findings did not reveal any significantly changing trend in the emergence of SSMR during the process. As a main trend, the number of notes included in SSMR threads differed significantly in different phases of the process and small groups differed from each other. Although student participation was seen as highly dispersed between the students, there were differences between students and small groups. Furthermore, the findings indicated that the amount of SSMR during the process or participation structure did not explain the differences in the quality of outcomes for the groups. Rather, when SSMRs were focused on understanding and procedural matters, it was associated with achieving high quality learning outcomes. In turn, when SSMRs were focused on incidental and procedural matters, it was associated with low level learning outcomes. Hence, the findings imply that the focus of any emerging SSMR is crucial to the quality of the learning outcomes. Moreover, the findings encourage the use of multiple research methods for studying SSMR. In total, the four studies convincingly indicate that a phenomenon of socially shared metacognitive regulation also exists. This means that it was possible to define the concept of SSMR theoretically, to investigate it methodologically and to validate it empirically in two different learning contexts across dyads and small groups. In-depth micro-level case analysis in Studies I and III showed the possibility to capture and analyse in detail SSMR during the collaborative process, while in Studies II and IV, the analysis validated the emergence of SSMR in larger data sets. Hence, validation was tested both between two environments and within the same environments with further cases. As a part of this dissertation, SSMR’s detailed functions and foci were revealed. Moreover, the findings showed the important role of observable metacognitive experiences as the starting point of SSMRs. It was apparent that problems dealt with by the groups should be rather difficult if SSMR is to be made clearly visible. Further, individual students’ participation was found to differ between students and groups. The multiple research methods employed revealed supplementary findings regarding SSMR. Finally, when SSMR was focused on understanding and procedural matters, this was seen to lead to higher quality learning outcomes. Socially shared metacognition regulation should therefore be taken into consideration in students’ collaborative learning at school similarly to how an individual’s metacognition is taken into account in individual learning.

Optimizing the Performance of a Heat Exchanger Network

This research is the continuation and a joint work with a master thesis that has been done in this department recently by Hemamali Chathurangani Yashika Jayathunga. The mathematical system of the equations in the designed Heat Exchanger Network synthesis has been extended by adding a number of equipment; such as heat exchangers, mixers and dividers. The solutions of the system is obtained and the optimal setting of the valves (Each divider contains a valve) is calculated by introducing grid-based optimization. Finding the best position of the valves will lead to maximization of the transferred heat in the hot stream and minimization of the pressure drop in the cold stream. The aim of the following thesis will be achieved by practicing the cost optimization to model an optimized network.

The functional fit between collaborative software and work systems:Qualification of work system needs to software functionality

The study develops an approach that tries to validate software functionality to work systems needs in SMEs. The formulated approach is constructed by using a SAAS based software i.e., work collaboration service (WCS), and SMEs as the elements of study. Where the WCS’s functionality is qualified to the collaboration needs that exist in operational and project work within SMEs. For this research constructivist approach and case study method is selected because the nature of the current study requires an in depth study of the work collaboration service as well as a detailed study of the work systems within different enterprises. Four different companies are selected in which fourteen interviews are conducted to gather data pertaining. The work systems method and framework are used as a central part of the approach to collect, analyze and interpret the enterprises work systems model and the underlying collaboration needs on operational and project work. On the other hand, the functional model of the WCS and its functionality is determined from functional model analysis, software testing, documentation and meetings with the service vendor. The enterprise work system model and the WCS model are compared to reveal how work progression differs between the two and make visible unaddressed stages of work progression. The WCS functionality is compared to work systems collaboration needs to ascertain if the service will suffice the needs of the project and operational work under study. The unaddressed needs provide opportunities to improve the functionality of the service for better conformity to the needs of enterprise and work. The results revealed that the functional models actually differed in how operational and project work progressed within the stages. WCS shared similar stages of work progression apart from the stages of identification and acceptance, and progress and completion stages were only partially addressed. Conclusion is that the identified unaddressed needs such as, single point of reference, SLA and OLA inclusion etc., should be implemented or improved within the WCS at appropriate stages of work to gain better compliance of the service to the needs of the enterprise an work itself. The developed approach can hence be used to carry out similar analysis for the conformance of pre-built software functionality to work system needs with SMEs.

Motives and barriers for engaging in collaborative consumption in Finland

In this thesis the consumers’ expected motives and barriers for engaging in collaborative consumption in Finland are studied. The phenomenon is observed through the lens of consumer theory and it is connected to the context using Hofstede’s 6-D model. The phenomenon is new and there are almost no recorded results in the background research, and when considering the limitations of this study, there are no results at all. Therefore, combining different kinds of literature, as well as taking along consumer theory and Hofstede’s model that explains cultural factors, it was possible to compile a comprehensive general view of the present state of the phenomenon. The actual study was conducted using qualitative methods and the solution was sought collecting data from six in-depth interviews with interviewees having experience from using, or offering resources, or both. According to the results, the primary motive in all modes of consumption was economic. Anti-materialism, anti-consumption, and expanding lifestyle were another a bit more general motives. Perceived barriers were, especially as a new result, the amount of trouble one has to see and in single modes, a lack of trust, the used platform and too expensive prices.

Value co-creation in bio-based chemicals value network

The purpose of this Master’s thesis is to study value co-creation in emerging value network. The main objective is to examine how value is co-created in bio-based chemicals value network. The study provides insights to different actors’ perceived value in the value network and enlightens their motivations to commit to the collaborative partnerships with other actors. Empirical study shows that value co-creation is creation of mutual value for both parties of the relationship by combining their non-competing resources to achieve a common goal. Value co-creation happens in interactions, and trust, commitment and information sharing are essential prerequisites for value co-creation. Value co-creation is not only common value creation, but it is also value that emerges for each actor because of the co-operation with the other actor. Even though the case companies define value mainly in economic terms, the other value elements like value of the partnership, knowledge transfer and innovation are more important for value co-creation.

Modelling the colour difference by artificial neural network

This thesis work studies the modelling of the colour difference using artificial neural network. Multilayer percepton (MLP) network is proposed to model CIEDE2000 colour difference formula. MLP is applied to classify colour points in CIE xy chromaticity diagram. In this context, the evaluation was performed using Munsell colour data and MacAdam colour discrimination ellipses. Moreover, in CIE xy chromaticity diagram just noticeable differences (JND) of MacAdam ellipses centres are computed by CIEDE2000, to compare JND of CIEDE2000 and MacAdam ellipses. CIEDE2000 changes the orientation of blue areas in CIE xy chromaticity diagram toward neutral areas, but on the whole it does not totally agree with the MacAdam ellipses. The proposed MLP for both modelling CIEDE2000 and classifying colour points showed good accuracy and achieved acceptable results.

The quality of the mother-child relationship during collaborative problem solving /

The quality of the mother-child relationship was examined in relation to joint planning, maternal teaching strategies, maternal emotional support, mutual positive affect and attachment security. Fifty-five grade five children and their mothers participated in a laboratory session comprised of various activities and completed questionnaires to evaluate attachment security. Joint planning and social problem solving were assessed observationally during an origami task. Problem solving effectiveness was unrelated to maternal teaching strategies, maternal encouragement and mutual positive affect. A marginally significant relationship was found between maternal encouragement and active child participation. Attachment security was found to be significantly related to sharing of responsibility during local planning, but only for child autonomous performance. An examination of conditional probabilities revealed that mutual positive affect did not increase the likelihood of subsequent mother-child dyadic regulation. However, mutual positive affect was found to be significantly related to both active child participation and dyadic regulation. The hypothesis predicting a mediational model was not supported. The implications of these findings in the theoretical and empirical literature were considered and suggestions for future research were made.

Collaborative reflection : supporting one practitioner's development of online learning communities /

This is a study of one participant's reflective practice as she worked to develop online communities in a face-to-face science course. Her process of reflective practice was examined in order to address factors that influenced her learning path, and the benefits and challenges of collaborative action research. These research goals were pursued using a collaborative action research methodology, initially chosen for its close match with Schon's (1983) model of reflective practice. The participant's learning fit vnth Mezirow's (1991) model of transformative learning. She began with beliefs that matched her goals, and she demonstrated significant learning in three areas. First, she demonstrated instrumental learning around the constraints of workload and time, and achieving online learning community indicators. Second, she demonstrated communicative learning that helped her to see her own needs for feedback and communication more clearly, and how other process partners had been a support to her. Third, her emancipatory learning saw her revisiting and questioning her goals. It was through the reflective conversation during the planned meetings and the researcher's reframing and interrogation of that reflection that the participant was able to clarify and extend her thinking, and in so doing, critically reflect on her practice as she worked to develop online learning communities. In this way, the collaborative action research methodology was an embodiment of co-constructivism through collaborative reflective practice. Schon's (1983) model of reflective practice positions a lone practitioners moving through cycles ofplan-act-observe-reflect. The results fi"om this study suggest that collaboration is an important piece of the reflective practice model.

Riffing on a Theme: Faculty Experiences With Service-Learning in a Food Security Research Network in Ontario

While service-learning is often said to be beneficial for all those involved—students, community members, higher education institutions, and faculty members—there are relatively few studies of the attraction to, and effect of, service-learning on faculty members. Existing studies have tended to use a survey design, and to be based in the United States. There is a lack of information on faculty experiences with service-learning in Ontario or Canada. This qualitative case study of faculty experiences with service-learning was framed through an Appreciative Inquiry social constructionist approach. The data were drawn from interviews with 18 faculty members who belong to a Food Security Research Network (FSRN) at a university in northern Ontario, reports submitted by the network, and personal observation of a selection of network-related events. This dissertation study revealed how involvement with service-learning created opportunities for faculty learning and growth. The focus on food security and a commitment to the sustainability of local food production was found to be an ongoing attraction to service-learning and a means to engage in and integrate research and teaching on matters of personal and professional importance to these faculty members. The dissertation concludes with a discussion of the FSRN’s model and the perceived value of a themed, transdisciplinary approach to service-learning. This study highlights promising practices for involving faculty in service-learning and, in keeping with an Appreciative Inquiry approach, depicts a view of faculty work at its best.