Feedback-related Brain Potential Activity Complies with Basic Assumptions of Associative Learning Theory

Feedback-related negativity (FRN) is an ERP component that distinguishes positive from negative feedback. FRN has been hypothesized to be the product of an error signal that may be used to adjust future behavior. In addition, associative learning models assume that the trial-to-trial learning of cueoutcome mappings involves the minimization of an error term. This study evaluated whether FRN is a possible electrophysiological correlate of this error term in a predictive learning task where human subjects were asked to learn different cueoutcome relationships. Specifically, we evaluated the sensitivity of the FRN to the course of learning when different stimuli interact or compete to become a predictor of certain outcomes. Importantly, some of these cues were blocked by more informative or predictive cues (i.e., the blocking effect). Interestingly, the present results show that both learning and blocking affect the amplitude of the FRN component. Furthermore, independent analyses of positive and negative feedback event-related signals showed that the learning effect was restricted to the ERP component elicited by positive feedback. The blocking test showed differences in the FRN magnitude between a predictive and a blocked cue. Overall, the present results show that ERPs that are related to feedback processing correspond to the main predictions of associative learning models. ■

'Situaciones problema' y desarrollo de la competencia motriz en educación física escolar: cuestiones didácticas = Problem situations and developing motor competence in Physical Education at school: didactic questions

From the areas of motor learning and the teaching of Physical Education we promote coherent methodological orientationswith the present curricular guide that are focused in such a way so that the student is able to act independently. In thissense we may consider the problem situations as a good example for methodological proposals. So as to determine its useand adequateness for Physical Education it is conveniente to analyse the characteristics of the motor tasks that areproposed as well as the features of the teaching intervention in such a way as to ease the adquisition and development ofthe motor competence of the students

Social competence and loneliness during the school years - Issues in assessment, interrelations and intergenerational transmission

Väitöskirjassa tarkastellaan kouluikäisten lasten ja nuorten sosiaalisen kompetenssin ja yksinäisyyden mittaamista, yhteyksiä ja periytyvyyttä vanhemmilta heidän lapsilleen. Alakouluikäisten lasten tutkimusaineisto (n=985) koostuu lapsilta itseltään, heidän luokkatovereiltaan, opettajiltaan ja vanhemmiltaan vuosina 2000 - 2004 osana Merkitystä etsimässä – tutkimusprojektia (M. Vauras) kerätystä aineistosta. Mukana on itse-, toveri-, opettaja- ja vanhempien arviot lasten sosiaalisesta kompetenssista, seuranta-aineisto lasten yksinäisyydestä, opettajien arviot lasten motivationaalisesta orientaatiosta, standardoiduin testisarjoin arvioidut akateemiset taidot sekä lasten äitien ja isien arviot omasta yksinäisyydestään ja koetusta kyvykkyydestään toimia vanhempana. Yläkouluikäisten nuorten (n=386) aineisto koostuu vuosina 2006 – 2007 osana Sosioemotionaalinen oppiminen ja hyvinvointi yläkouluyhteisössä (P. M. Niemi) kerätystä nuorten yksinäisyyden, sosiaalisen ahdistuneisuuden ja sosiaalisen fobian seuranta-aineistosta. Mitattavuutta (päätavoite 1) tutkittiin erityisesti monitahoarviointien rakenteiden yhtenäisyyksiä, subjektiivisten arvioiden ajallista pysyvyyttä sekä mittareiden validiteettia ja reliabiliteettia testaamalla. Sosiaalisen kompetenssin ja yksinäisyyden keskinäisten yhteyksien lisäksi tarkasteltiin näiden yhteyttä alakoululaisten oppimiseen sekä yläkou¬lulaisten psykososiaaliseen hyvinvointiin (päätavoite 2). Kolmantena päätavoitteena oli selvittää yksinäisyyden mahdollista periytymistä vanhemmilta lapsille. Osana ensimmäistä päätavoitetta kehitettiin Monitahoarviointi sosiaalisesta kompetenssista (MASK) -arviointimenetelmä (artikkeli 1). Konfirmatorisen faktorianalyysin tulosten perusteella nelifaktorinen rakenne (prososiaalisuus sisältäen yhteistyötaidot ja empatiakyvyn sekä antisosiaalisuus sisältäen impulsiivisuuden ja häiritsevyyden) sopi sekä lasten itsensä, heidän luokkatovereidensa, opettajiensa että vanhempiensa tekemiin arviointeihin. Eri tahojen arviointien väliset korrelaatiot olivat tilastollisesti merkitseviä, joskin suhteellisen matalia, ts. eri tahojen näkökulmat lapsen sosiaalisesta kompetenssista ovat toisistaan eriäviä. Täten eri arvioitsijatahojen käyttäminen on kokonaisuuden tutkimisen kannalta tärkeää. Toisena mittaamiseen liittyvänä tavoitteena oli validoida Hozan, Bukowskin ja Beeryn (2000) sosiaalisen ja emotionaalisen yksinäisyyden mittari suomalaisille lapsille (artikkeli 3) ja nuorille (artikkeli 4) soveltuvaksi sekä tutkia, ovatko lasten ja nuorten arviot omasta yksinäisyydestään ajallisesti pysyviä. Alakoululaisten lasten osalta yksinäisyys, erityisesti sosiaalinen yksinäisyys osoittautui suhteellisen pysyväksi, mutta vahvistui entisestään yläkouluikäisten nuorten aineistoa tarkasteltaessa. Huomionarvoista sekä ala- että yläkoululaisten aineistoissa oli poikien kokema vahva emotionaalinen yksinäisyys. Molempien mittareiden osalta sekä validiteetti että reliabiliteetti todettiin hyväksyttäväksi ja niitä voidaan suositella lasten ja nuorten sosiaalisen kompetenssin ja yksinäisyyden arviointimenetelmiksi. Toisena päätavoitteena oli rakenneyhtälömallinnuksen keinoin tarkastella sosiaalisen kompetenssin ja yksinäisyyden yhteyksiä sekä keskenään (artikkelit 2 ja 3) että suhteessa lasten oppimiseen (artikkeli 2) ja nuorten psykososiaaliseen hyvinvointiin (artikkeli 4). Alakouluikäisten lasten osalta sosiaalinen kompetenssi oli yhteydessä pait¬si yksinäisyyteen myös opettajien oppilaistaan tekemiin motivationaalisen orientaation arvioihin sekä standardoiduin testien arvioituihin akateemisiin taitoihin. Yläkouluikäisten nuorten osalta yksinäisyys oli yhteydessä sosiaaliseen ahdistuneisuuteen ja sosiaaliseen fobiaan. Täten sosiaalisen kompetenssin voidaan katsoa olevan koululaisten hyvinvointia ja oppimista vahvistava, ja toisaalta yksinäisyyden nuorten psykososiaalista hyvinvointia heikentävä tekijä. Viimeisenä päätavoitteena mallinnettiin yksinäisyyden mahdollista periytyvyyttä. Ensimmäisessä vaiheessa periytyvyyttä tarkasteltiin koko perheen sisällä, vanhempien tai lasten sukupuolta erottelematta (artikkeli 2). Tässä rakenneyhtälömallissa vanhempien kokema yksinäisyys ennusti heikompaa kyvykkyydentunnetta vanhemmuudesta, joka edelleen ennusti lapsen heikompaa toveriarvioitua sosiaalista kompetenssia koulussa ja tätä kautta vahvempaa yksinäisyyden kokemusta. Toisessa mallissa eroteltiin äitien ja isien sekä tyttöjen ja poikien aineistot, jotta periytyvyyttä voitiin tarkastella äiti-tytär, äiti-poika, isä-tytär ja isä-poika dyadisuhteissa. Rakenneyhtälömallinnuksen tulosten perusteella sekä äitien että isien kokema yksinäisyys ennusti

Learning Robot Motions from Visual Sensing

Learning from demonstration becomes increasingly popular as an efficient way of robot programming. Not only a scientific interest acts as an inspiration in this case but also the possibility of producing the machines that would find application in different areas of life: robots helping with daily routine at home, high performance automata in industries or friendly toys for children. One way to teach a robot to fulfill complex tasks is to start with simple training exercises, combining them to form more difficult behavior. The objective of the Master’s thesis work was to study robot programming with visual input. Dynamic movement primitives (DMPs) were chosen as a tool for motion learning and generation. Assuming a movement to be a spring system influenced by an external force, making this system move, DMPs represent the motion as a set of non-linear differential equations. During the experiments the properties of DMP, such as temporal and spacial invariance, were examined. The effect of the DMP parameters, including spring coefficient, damping factor, temporal scaling, on the trajectory generated were studied.

Neural correlates of language learning in adults

The human language-learning ability persists throughout life, indicating considerable flexibility at the cognitive and neural level. This ability spans from expanding the vocabulary in the mother tongue to acquisition of a new language with its lexicon and grammar. The present thesis consists of five studies that tap both of these aspects of adult language learning by using magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) during language processing and language learning tasks. The thesis shows that learning novel phonological word forms, either in the native tongue or when exposed to a foreign phonology, activates the brain in similar ways. The results also show that novel native words readily become integrated in the mental lexicon. Several studies in the thesis highlight the left temporal cortex as an important brain region in learning and accessing phonological forms. Incidental learning of foreign phonological word forms was reflected in functionally distinct temporal lobe areas that, respectively, reflected short-term memory processes and more stable learning that persisted to the next day. In a study where explicitly trained items were tracked for ten months, it was found that enhanced naming-related temporal and frontal activation one week after learning was predictive of good long-term memory. The results suggest that memory maintenance is an active process that depends on mechanisms of reconsolidation, and that these process vary considerably between individuals. The thesis put special emphasis on studying language learning in the context of language production. The neural foundation of language production has been studied considerably less than that of perceptive language, especially on the sentence level. A well-known paradigm in language production studies is picture naming, also used as a clinical tool in neuropsychology. This thesis shows that accessing the meaning and phonological form of a depicted object are subserved by different neural implementations. Moreover, a comparison between action and object naming from identical images indicated that the grammatical class of the retrieved word (verb, noun) is less important than the visual content of the image. In the present thesis, the picture naming was further modified into a novel paradigm in order to probe sentence-level speech production in a newly learned miniature language. Neural activity related to grammatical processing did not differ between the novel language and the mother tongue, but stronger neural activation for the novel language was observed during the planning of the upcoming output, likely related to more demanding lexical retrieval and short-term memory. In sum, the thesis aimed at examining language learning by combining different linguistic domains, such as phonology, semantics, and grammar, in a dynamic description of language processing in the human brain.

Group mentoring for junior medical students: perceptions of mentees and mentors

Entering medical school can be associated with a number of difficulties that can hinder students' performance. Mentoring programs are designed to help students circumvent difficulties and improve their learning and personal development. The current study aimed to evaluate the perceptions of both students and mentors regarding a recently introduced, group-based mentoring program designed to support first-year students. After one year of regular meetings, students and mentors' perceptions of the program were assessed by means of structured questionnaires. Response content categories were identified through multiple readings. Both regular attendees and non-participating students had positive opinions about the program. Mentors were highly satisfied at having participated and acknowledged that the program has been useful not only for assisting students, but also for fostering their own personal and professional development. In conclusion, the group-based mentoring program is feasible and can elicit positive views from both mentors and students. In addition, faculty members' participation as mentors can also be beneficial, since the program appears to contribute to their own personal and professional development

Organizational learning from customer interaction

In the fierce competition of today‟s business world an organization‟s capacity to learn maybe its only competitive advantage. This research aims at increasing the understanding on how organizational learning from the customer happens in technology companies. In doing so it provides a synthesized definition of organizational learning and investigates processes of organizational learning within technology companies. A qualitative research method and in-depth interviews with different sized high technology companies, as applied here, enables in-depth study of the learning processes. Research contributes to the understanding of what type of knowledge firms acquire, how new knowledge is transferred and used in a learning firm‟s routines and processes. Research findings show that SMEs and large size companies also, depending on their position in the software value chain, consider different knowledge types as most important and that they use different learning methods to acquire knowledge from their customers.

Researching Manufacturing Planning and Control system and Master Scheduling in a manufacturing firm.

The objective of this thesis is to research Manufacturing Planning and Control (MPC) system and Master Scheduling (MS) in a manufacturing firm. The study is conducted at Ensto Finland Corporation, which operates on a field of electrical systems and supplies. The paper consists of theoretical and empirical parts. The empirical part is based on weekly operating at Ensto and includes inter-firm material analysis, learning and meetings. Master Scheduling is an important module of an MPC system, since it is beneficial on transforming strategic production plans based on demand forecasting into operational schedules. Furthermore, capacity planning tools can remarkably contribute to production planning: by Rough-Cut Capacity Planning (RCCP) tool, a MS plan can be critically analyzed in terms of available key resources in real manufacturing environment. Currently, there are remarkable inefficiencies when it comes to Ensto’s practices: the system is not able to take into consideration seasonal demand and react on market changes on time; This can cause significant lost sales. However, these inefficiencies could be eliminated through the appropriate utilization of MS and RCCP tools. To utilize MS and RCCP tools in Ensto’s production environment, further testing in real production environment is required. Moreover, data accuracy, appropriate commitment to adapting and learning the new tools, and continuous developing of functions closely related to MS, such as sales forecasting, need to be ensured.

Socially Competent Leadership - predictors, impacts and skilling in engineering

Earlier management studies have found a relationship between managerial qualities and subordinate impacts, but the effect of managers‘ social competence on leader perceptions has not been solidly established. To fill the related research gap, the present work embarks on a quantitative empirical effort to identify predictors of successful leadership. In particular, this study investigates relationships between perceived leader behavior and three selfreport instruments used to measure managerial capability: 1) the WOPI Work Personality Inventory, 2) Raven‘s general intelligence scale, and 3) the Emotive Communication Scale (ECS). This work complements previous research by resorting to both self-reports and other-reports: the results acquired from the managerial sample are compared to subordinate perceptions as measured through the ECS other-report and the WOPI360 multi-source appraisal. The quantitative research is comprised of a sample of 8o superiors and 354 subordinates operating in eight Finnish organizations. The strongest predictive value emerged from the ECS self- and other-reports and certain personality dimensions. In contrast, supervisors‘ logical intelligence did not correlate with leadership perceived as socially competent by subordinates. 16 of the superiors rated as most socially competent by their subordinates were selected for case analysis. Their qualitative narratives evidence the role of life history and post-traumatic growth in developing managerial skills. The results contribute to leadership theory in four ways. First, the ECS self-report devised for this research offers a reliable scale for predicting socially competent leader ability. Second, the work identifies dimensions of personality and emotive skills that can be considered predictors of managerial ability and benefited from in leader recruitment and career planning. Third, the Emotive Communication Model delineated on the basis of the empirical data allows for a systematic design and planning of communication and leadership education. Fourth, this workfurthers understanding of personal growth strategies and the role of life history in leader development and training. Finally, this research advances educational leadership by conceptualizing and operationalizing effective managerial communications. The Emotive Communication Model devised directs the pedagogic attention in engineering to assertion, emotional availability and inspiration skills. The proposed methodology addresses classroom management strategies drawing from problem-based learning, student empowerment, collaborative learning, and so-called socially competent teachership founded on teacher immediacy and perceived caring, all constituting strategies moving away from student compliance and teacher modelling. The ultimate educational objective embraces the development of individual engineers and organizational leaders that not only possess traditional analytical and technical expertise and substantive knowledge but are intelligent also creatively, practically, and socially.

Thinking Outside the Box: Enhancing Science Teaching by Combining (Instead of Contrasting) Laboratory and Simulation Activities

The focus of the present work was on 10- to 12-year-old elementary school students’ conceptual learning outcomes in science in two specific inquiry-learning environments, laboratory and simulation. The main aim was to examine if it would be more beneficial to combine than contrast simulation and laboratory activities in science teaching. It was argued that the status quo where laboratories and simulations are seen as alternative or competing methods in science teaching is hardly an optimal solution to promote students’ learning and understanding in various science domains. It was hypothesized that it would make more sense and be more productive to combine laboratories and simulations. Several explanations and examples were provided to back up the hypothesis. In order to test whether learning with the combination of laboratory and simulation activities can result in better conceptual understanding in science than learning with laboratory or simulation activities alone, two experiments were conducted in the domain of electricity. In these experiments students constructed and studied electrical circuits in three different learning environments: laboratory (real circuits), simulation (virtual circuits), and simulation-laboratory combination (real and virtual circuits were used simultaneously). In order to measure and compare how these environments affected students’ conceptual understanding of circuits, a subject knowledge assessment questionnaire was administered before and after the experimentation. The results of the experiments were presented in four empirical studies. Three of the studies focused on learning outcomes between the conditions and one on learning processes. Study I analyzed learning outcomes from experiment I. The aim of the study was to investigate if it would be more beneficial to combine simulation and laboratory activities than to use them separately in teaching the concepts of simple electricity. Matched-trios were created based on the pre-test results of 66 elementary school students and divided randomly into a laboratory (real circuits), simulation (virtual circuits) and simulation-laboratory combination (real and virtual circuits simultaneously) conditions. In each condition students had 90 minutes to construct and study various circuits. The results showed that studying electrical circuits in the simulation–laboratory combination environment improved students’ conceptual understanding more than studying circuits in simulation and laboratory environments alone. Although there were no statistical differences between simulation and laboratory environments, the learning effect was more pronounced in the simulation condition where the students made clear progress during the intervention, whereas in the laboratory condition students’ conceptual understanding remained at an elementary level after the intervention. Study II analyzed learning outcomes from experiment II. The aim of the study was to investigate if and how learning outcomes in simulation and simulation-laboratory combination environments are mediated by implicit (only procedural guidance) and explicit (more structure and guidance for the discovery process) instruction in the context of simple DC circuits. Matched-quartets were created based on the pre-test results of 50 elementary school students and divided randomly into a simulation implicit (SI), simulation explicit (SE), combination implicit (CI) and combination explicit (CE) conditions. The results showed that when the students were working with the simulation alone, they were able to gain significantly greater amount of subject knowledge when they received metacognitive support (explicit instruction; SE) for the discovery process than when they received only procedural guidance (implicit instruction: SI). However, this additional scaffolding was not enough to reach the level of the students in the combination environment (CI and CE). A surprising finding in Study II was that instructional support had a different effect in the combination environment than in the simulation environment. In the combination environment explicit instruction (CE) did not seem to elicit much additional gain for students’ understanding of electric circuits compared to implicit instruction (CI). Instead, explicit instruction slowed down the inquiry process substantially in the combination environment. Study III analyzed from video data learning processes of those 50 students that participated in experiment II (cf. Study II above). The focus was on three specific learning processes: cognitive conflicts, self-explanations, and analogical encodings. The aim of the study was to find out possible explanations for the success of the combination condition in Experiments I and II. The video data provided clear evidence about the benefits of studying with the real and virtual circuits simultaneously (the combination conditions). Mostly the representations complemented each other, that is, one representation helped students to interpret and understand the outcomes they received from the other representation. However, there were also instances in which analogical encoding took place, that is, situations in which the slightly discrepant results between the representations ‘forced’ students to focus on those features that could be generalised across the two representations. No statistical differences were found in the amount of experienced cognitive conflicts and self-explanations between simulation and combination conditions, though in self-explanations there was a nascent trend in favour of the combination. There was also a clear tendency suggesting that explicit guidance increased the amount of self-explanations. Overall, the amount of cognitive conflicts and self-explanations was very low. The aim of the Study IV was twofold: the main aim was to provide an aggregated overview of the learning outcomes of experiments I and II; the secondary aim was to explore the relationship between the learning environments and students’ prior domain knowledge (low and high) in the experiments. Aggregated results of experiments I & II showed that on average, 91% of the students in the combination environment scored above the average of the laboratory environment, and 76% of them scored also above the average of the simulation environment. Seventy percent of the students in the simulation environment scored above the average of the laboratory environment. The results further showed that overall students seemed to benefit from combining simulations and laboratories regardless of their level of prior knowledge, that is, students with either low or high prior knowledge who studied circuits in the combination environment outperformed their counterparts who studied in the laboratory or simulation environment alone. The effect seemed to be slightly bigger among the students with low prior knowledge. However, more detailed inspection of the results showed that there were considerable differences between the experiments regarding how students with low and high prior knowledge benefitted from the combination: in Experiment I, especially students with low prior knowledge benefitted from the combination as compared to those students that used only the simulation, whereas in Experiment II, only students with high prior knowledge seemed to benefit from the combination relative to the simulation group. Regarding the differences between simulation and laboratory groups, the benefits of using a simulation seemed to be slightly higher among students with high prior knowledge. The results of the four empirical studies support the hypothesis concerning the benefits of using simulation along with laboratory activities to promote students’ conceptual understanding of electricity. It can be concluded that when teaching students about electricity, the students can gain better understanding when they have an opportunity to use the simulation and the real circuits in parallel than if they have only the real circuits or only a computer simulation available, even when the use of the simulation is supported with the explicit instruction. The outcomes of the empirical studies can be considered as the first unambiguous evidence on the (additional) benefits of combining laboratory and simulation activities in science education as compared to learning with laboratories and simulations alone.

The role of business information and knowledge in sales steering

The objective of this study is to find out how sales management can be optimally supported with business information and knowledge. The first chapters of the study focus on theoretical literature about sales planning, sales steering, business intelligence, and knowledge management. The empirical part of the study is a case study for which the material was collected through interviews with the selected people of the company. The findings from the interviews were analyzed, and possible suggestions for solving the problems were made. The case study revealed that sales management requires a multitude of metrics and reports to steer the sales to the desired direction. The information sources can be internal and external, and the optimal solution for satisfying the information needs is a combination of both of these. The simple information should be turned into knowledge by merging the intellectual assets with the information from the firm’s transaction processing systems, in order to promote organizational learning and effective decision-making.

The nature of communication structures of university students in an international web-based computer-supported collaborative learning (CSCL) course

Communication, the flow of ideas and information between individuals in a social context, is the heart of educational experience. Constructivism and constructivist theories form the foundation for the collaborative learning processes of creating and sharing meaning in online educational contexts. The Learning and Collaboration in Technology-enhanced Contexts (LeCoTec) course comprised of 66 participants drawn from four European universities (Oulu, Turku, Ghent and Ramon Llull). These participants were split into 15 groups with the express aim of learning about computer-supported collaborative learning (CSCL). The Community of Inquiry model (social, cognitive and teaching presences) provided the content and tools for learning and researching the collaborative interactions in this environment. The sampled comments from the collaborative phase were collected and analyzed at chain-level and group-level, with the aim of identifying the various message types that sustained high learning outcomes. Furthermore, the Social Network Analysis helped to view the density of whole group interactions, as well as the popular and active members within the highly collaborating groups. It was observed that long chains occur in groups having high quality outcomes. These chains were also characterized by Social, Interactivity, Administrative and Content comment-types. In addition, high outcomes were realized from the high interactive cases and high-density groups. In low interactive groups, commenting patterned around the one or two central group members. In conclusion, future online environments should support high-order learning and develop greater metacognition and self-regulation. Moreover, such an environment, with a wide variety of problem solving tools, would enhance interactivity.

The key practices of customer portfolio management (CPM) process in the medical and healthcare B2B industry

The goal of this study is to deepen the understanding of the customer portfolio management process. There are many models for the process, and they are not necessarily exclusive of each other. Consequently, the inclusion of many models might even prove out to be beneficial. Other theoretical framework include the current economical situation and its propose on customer portfolio management. With an understanding of the theoretical models as a background, the empirical part of this study compares Finnish multinational medical and healthcare technology companies’ customer portfolio management practices. The empirical research was carried out with theme interviews held with 11 sales and marketing managers or directors from four different companies. The goal was to discover the most essential practices of the process steps in the companies. The result of this study is that there is a lack of systematic customer portfolio management, but most companies are aiming to improve this in the near future. The most essential practices are analysis of sales, communication level, learning, and commitment to strategy of the focal company. Special characteristics of this industry include large business networks that include customers, professional end-users, institutions, universities, researchers, and key opinion leaders. The management and analysis of this comprehensive network has been seen to be extremely important for this industry.

Corporate Social Responsibility and Shipping Views of Baltic Sea Shipping Companies on the Benefits of Responsibility

The safety of shipping operations in the Baltic Sea is an extensively studied issue due to the density of traffic and the ecological sensitivity of the area. The focus has, however, mainly been on ship technology or on traffic control measures and the operative safety aspect of shipping is in a minor position in maritime safety studies and is lacking in terms of solutions. Self-regulatory and voluntary measures could be effective ways to improve the operational safety of shipping. Corporate social responsibility, or CSR, is one example of a voluntary measure that the shipping companies can take. CSR can enhance maritime safety and improve the shipping companies’ competitiveness. The aim of this study is to increase the knowledge of CSR in the maritime sector and study its applicability and benefits to the shipping companies. The research comprises of a theory part and a questionnaire study, which examine the significance of corporate social responsibility in shipping companies’ maritime safety and competitiveness. The aim of the questionnaire study is to find out how corporate social responsibility is implemented in the shipping companies. According to the literature review, responsible actions can produce financial and time costs, but due to these actions cost savings in the form of learning and increased efficiency can be achieved. Responsible actions can also produce concrete improvements and a reputation of responsibility that can lead to both cost savings and increase in the company’s income. CSR is recognised as having real business benefits in terms of attracting customers and high-quality employees. In shipping, CSR usually focuses on environmental issues. Environmental social responsibility in shipping is mainly motivated by the need to comply with existing and forthcoming regulation. Shipping companies engage in CSR to gain competitive advantage and to increase maritime safety. The social aspects of CSR take into account the well-being and skills of the employees, corporation and other stakeholders of the company. The questionnaire study revealed that the most common CSR measures in shipping companies are environmental measures, and that environmental concerns are considered to be the most important reason to engage in CSR. From the preliminary question about the concept of CSR it can also be seen that safety issues are commonly considered to be a part of CSR and safety gains are the second most important reason to engage in CSR. From the questionnaire, it can also be extrapolated that gaining a better reputation is one of the most important reasons to engage in CSR in the first place. For example, the main economic benefit was seen to be the increase of customer numbers as a result of a better reputation. Based on the study, it would seem that companies are starting to realise that they might gain competitive advantage and be favoured as shippers if they engage in sustainable, responsible operations and present themselves as “green”.

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.