Estimating microalgae Synechococcus nidulans daily biomass concentration using neuro-fuzzy network

In this study, a neuro-fuzzy estimator was developed for the estimation of biomass concentration of the microalgae Synechococcus nidulans from initial batch concentrations, aiming to predict daily productivity. Nine replica experiments were performed. The growth was monitored daily through the culture medium optic density and kept constant up to the end of the exponential phase. The network training followed a full 3³ factorial design, in which the factors were the number of days in the entry vector (3,5 and 7 days), number of clusters (10, 30 and 50 clusters) and internal weight softening parameter (Sigma) (0.30, 0.45 and 0.60). These factors were confronted with the sum of the quadratic error in the validations. The validations had 24 (A) and 18 (B) days of culture growth. The validations demonstrated that in long-term experiments (Validation A) the use of a few clusters and high Sigma is necessary. However, in short-term experiments (Validation B), Sigma did not influence the result. The optimum point occurred within 3 days in the entry vector, 10 clusters and 0.60 Sigma and the mean determination coefficient was 0.95. The neuro-fuzzy estimator proved a credible alternative to predict the microalgae growth.

Luonnonhaltijat ‒ haltijoita luonnonympäristössä? : Nature spirits : continuity and change : Conference of Belief Narrative Network of ISFNR, Zugdidi, Georgia 1.‒4.10.2014

Konferenssiraportti

Electrical Safety of Island Operated Low Voltage DC Network

Today, renewable energy technologies and modern power electronics have made it feasible to implement low voltage direct current (LVDC) microgrids (MGs) ca-pable to island operation. Such LVDC networks are particularly useful in remote areas. However, there are still pending issues in island operated LVDC MGs like electrical safety and controlled operation, which should be addressed before wide-scale implementation. This thesis is focused on the overall protection of an island operated LVDC network concept, including protection against electrical shocks, mains equipment protection and protection of photovoltaic (PV) power sources and battery energy storage systems (BESSs). The topic is approached through ex-amination of the safety hazards and the appropriate methods to protect against them, comprising considerations for earthing system selection and realisation of the protection system.

Survival competencies in SMEs in changing business environments

The thesis examines the competencies that enable business survival in changing business environments from the perspective of Russian and Finnish micro, small, and medium-sized enterprises in the field of forest industry. Additionally, it studies the competence transformation necessary in SMEs for successful continuation of business operations when a firm considers transferring its business to another industry. The dissertation builds a holistic firm-level view of survival competencies for SMEs facing changes in their business environments. The holistic firm-level view of competencies includes both the individual-level and the firm-level perspectives, regardless of the position of the person in a firm. The findings highlight the importance of high-level individual competencies and the ability to perform versatile tasks in a firm. In addition, continuous business environment scanning, self-evaluation of personal competencies, willingness to renew and change, open-mindedness, and a readiness to network, are competencies that belong to and need to be taken care of by everybody – employees and employers - in a firm. In addition to previous competencies, an ability to manage every-day business also needs to be embedded in SME owners/managers. Furthermore, Russian SMEs seem to be more proactive in change situations, when compared with Finnish SMEs, which are used to operate in a more stable business environment. In conclusion, it can be said that the thesis adds to SME literature by introducing the concept of ‘SME-level competencies’, a combination of previously discussed organisational and networking competencies which are needed in order to survive through change. Furthermore, the thesis concludes with new competence classifications, such as operational and change competencies, which offer new information concerning the required competencies by which a firm may reduce the resistance to change that can hinder business renewal. For SME practitioners, the study suggests proper preparation and proactive operations in their business to reduce the influence of endless changes, and reminds SME owners/managers that changes are, however, a significant source of new business opportunities. For educational players, the study suggests upgrading educational and training systems by improving the training as regards attitudes towards work, and especially training in the comprehensive working abilities needed in SMEs to master diverse tasks. Finally, for public actors the study suggests providing stronger support to entrepreneurs by boosting SMEs entrepreneurial conditions and the existing business possibilities in change situations. This can be done by encouraging a legislative and entrepreneurial climate that responds better to the demands of SMEs.

Strategy and Superior Competence of Growth Company

This thesis is an examination of growth company and it's superior competence and performance which is based on existing theories and research findings. The theory framework is a basis for the processing part of the thesis that is utilized and combined into new thoughts and assumptions. The analysis is focused on the strategy's meaning, the content of strategy, strategy management, strategy planning, strategy tools and methods. The most important finding and discovery were that the strategy and superior competence / performance of successful growth company are rather a continuously improving process and a lifestyle than for example annual strategy project and/or separate strategy seasons.

Responding to Changing Student Demographics in Finland: A Study of Teachers’ Developing Cultural Competence

The aim of this dissertation was to examine the skills and knowledge that pre-service teachers and teachers have and need about working with multilingual and multicultural students from immigrant backgrounds. The specific goals were to identify pre-service teachers’ and practising teachers’ current knowledge and awareness of culturally and linguistically responsive teaching, identify a profile of their strengths and needs, and devise appropriate professional development support and ways to prepare teachers to become equitable culturally responsive practitioners. To investigate these issues, the dissertation reports on six original empirical studies within two groups of teachers: international pre-service teacher education students from over 25 different countries as well as pre-service and practising Finnish teachers. The international pre-service teacher sample consisted of (n = 38, study I; and n = 45, studies II-IV) and the pre-service and practising Finnish teachers sample encompassed (n = 89, study V; and n = 380, study VI). The data used were multi-source including both qualitative (students’ written work from the course including journals, final reflections, pre- and post-definition of key terms, as well as course evaluation and focus group transcripts) and quantitative (multi-item questionnaires with open-ended options), which enhanced the credibility of the findings resulting in the triangulation of data. Cluster analytic procedures, multivariate analysis of variance (MANOVA), and qualitative analyses mostly Constant Comparative Approach were used to understand pre-service teachers’ and practising teachers’ developing cultural understandings. The results revealed that the mainly white / mainstream teacher candidates in teacher education programmes bring limited background experiences, prior socialisation, and skills about diversity. Taking a multicultural education course where identity development was a focus, positively influenced teacher candidates’ knowledge and attitudes toward diversity. The results revealed approaches and strategies that matter most in preparing teachers for culturally responsive teaching, including but not exclusively, small group activities and discussions, critical reflection, and field immersion. This suggests that there are already some tools to address the need for the support needed to teach successfully a diversity of pupils and provide in-service training for those already practising the teaching profession. The results provide insight into aspects of teachers’ knowledge about both the linguistic and cultural needs of their students, as well as what constitutes a repertoire of approaches and strategies to assure students’ academic success. Teachers’ knowledge of diversity can be categorised into sound awareness, average awareness, and low awareness. Knowledge of diversity was important in teachers’ abilities to use students’ language and culture to enhance acquisition of academic content, work effectively with multilingual learners’ parents/guardians, learn about the cultural backgrounds of multilingual learners, link multilingual learners’ prior knowledge and experience to instruction, and modify classroom instruction for multilingual learners. These findings support the development of a competency based model and can be used to frame the studies of pre-service teachers, as well as the professional development of practising teachers in increasingly diverse contexts. The present set of studies take on new significance in the current context of increasing waves of migration to Europe in general and Finland in particular. They suggest that teacher education programmes can equip teachers with the necessary attitudes, skills, and knowledge to enable them work effectively with students from different ethnic and language backgrounds as they enter the teaching profession. The findings also help to refine the tools and approaches to measuring the competencies of teachers teaching in mainstream classrooms and candidates in preparation.

Item-level life-cycle model for maintenance network – from cost to additional value

The importance of industrial maintenance has been emphasized during the last decades; it is no longer a mere cost item, but one of the mainstays of business. Market conditions have worsened lately, investments in production assets have decreased, and at the same time competition has changed from taking place between companies to competition between networks. Companies have focused on their core functions and outsourced support services, like maintenance, above all to decrease costs. This new phenomenon has led to increasing formation of business networks. As a result, a growing need for new kinds of tools for managing these networks effectively has arisen. Maintenance costs are usually a notable part of the life-cycle costs of an item, and it is important to be able to plan the future maintenance operations for the strategic period of the company or for the whole life-cycle period of the item. This thesis introduces an itemlevel life-cycle model (LCM) for industrial maintenance networks. The term item is used as a common definition for a part, a component, a piece of equipment etc. The constructed LCM is a working tool for a maintenance network (consisting of customer companies that buy maintenance services and various supplier companies). Each network member is able to input their own cost and profit data related to the maintenance services of one item. As a result, the model calculates the net present values of maintenance costs and profits and presents them from the points of view of all the network members. The thesis indicates that previous LCMs for calculating maintenance costs have often been very case-specific, suitable only for the item in question, and they have also been constructed for the needs of a single company, without the network perspective. The developed LCM is a proper tool for the decision making of maintenance services in the network environment; it enables analysing the past and making scenarios for the future, and offers choices between alternative maintenance operations. The LCM is also suitable for small companies in building active networks to offer outsourcing services for large companies. The research introduces also a five-step constructing process for designing a life-cycle costing model in the network environment. This five-step designing process defines model components and structure throughout the iteration and exploitation of user feedback. The same method can be followed to develop other models. The thesis contributes to the literature of value and value elements of maintenance services. It examines the value of maintenance services from the perspective of different maintenance network members and presents established value element lists for the customer and the service provider. These value element lists enable making value visible in the maintenance operations of a networked business. The LCM added with value thinking promotes the notion of maintenance from a “cost maker” towards a “value creator”.

Optimization of Transportation System by Tailored Logistics Network: A Case Study in Automotive Industry

This thesis aims to redesign the supply chain system in an automotive industry in order to obtain space reduction in the inventory by using tailored logistics network. The redesigning process by tailored supply chain will combine all possible shipment methods including direct shipment, milk-run, milk-run via distribution center and Kanban delivery. The current supply chain system in Nissan goes rather well when the production volume is in moderate level. However, when the production volume is high, there is a capacity problem in the warehouse to accommodate all delivered parts from suppliers. Hence, the optimization of supply chain system is needed in order to obtain efficient logistics process and effective inventory consumption. The study will use primary data for both qualitative and quantitative approach as the research methods. Qualitative data will be collected by conducting interviews with people related to procurement and inventory control. Quantitative data consists of list of suppliers with their condition in several parameters which will be evaluated and analyzed by using scoring method to assign the most suitable transportation network to each suppliers for improvement of inventory reduction in a cost efficient manner.

Sustainable sourcing in global supply network: assessment of geographic challenges and management methods Case: Stora Enso

The purpose of this work was to describe and compare sourcing practices and challenges in different geographies, to discuss possible options to advance sustainability of global sourcing, and to provide examples to answer why sourcing driven by sustainability principles is so challenging to implement. The focus was on comparison between Europe & Asia & South-America from the perspective of sustainability adoption. By analyzing sourcing practices of the case company it was possible to describe main differences and challenges of each continent, available sourcing options, supplier relationships and ways to foster positive chance. In this qualitative case study gathered theoretical material was compared to extensive sourcing practices of case company in a vast supplier network. Sourcing specialist were interviewed and information provided by them analyzed in order to see how different research results and theories are reflecting reality and to find answers to proposed research questions.

Evaluation of Machine Learning Classifiers for Mobile Network Intrusion Detection Systems

Mobile malwares are increasing with the growing number of Mobile users. Mobile malwares can perform several operations which lead to cybersecurity threats such as, stealing financial or personal information, installing malicious applications, sending premium SMS, creating backdoors, keylogging and crypto-ransomware attacks. Knowing the fact that there are many illegitimate Applications available on the App stores, most of the mobile users remain careless about the security of their Mobile devices and become the potential victim of these threats. Previous studies have shown that not every antivirus is capable of detecting all the threats; due to the fact that Mobile malwares use advance techniques to avoid detection. A Network-based IDS at the operator side will bring an extra layer of security to the subscribers and can detect many advanced threats by analyzing their traffic patterns. Machine Learning(ML) will provide the ability to these systems to detect unknown threats for which signatures are not yet known. This research is focused on the evaluation of Machine Learning classifiers in Network-based Intrusion detection systems for Mobile Networks. In this study, different techniques of Network-based intrusion detection with their advantages, disadvantages and state of the art in Hybrid solutions are discussed. Finally, a ML based NIDS is proposed which will work as a subsystem, to Network-based IDS deployed by Mobile Operators, that can help in detecting unknown threats and reducing false positives. In this research, several ML classifiers were implemented and evaluated. This study is focused on Android-based malwares, as Android is the most popular OS among users, hence most targeted by cyber criminals. Supervised ML algorithms based classifiers were built using the dataset which contained the labeled instances of relevant features. These features were extracted from the traffic generated by samples of several malware families and benign applications. These classifiers were able to detect malicious traffic patterns with the TPR upto 99.6% during Cross-validation test. Also, several experiments were conducted to detect unknown malware traffic and to detect false positives. These classifiers were able to detect unknown threats with the Accuracy of 97.5%. These classifiers could be integrated with current NIDS', which use signatures, statistical or knowledge-based techniques to detect malicious traffic. Technique to integrate the output from ML classifier with traditional NIDS is discussed and proposed for future work.