Value creation in intelligent packaging value chains

The goal of this thesis is to look for and point out problems and bottlenecks related to value chains and networks in initiation and implementation of intelligent packaging. The research is based on interviews in different case companies and is qualitative by nature. The interview results are examined through a framework built upon relevant theory, with the aim to present a useful recommendation for a supplier company for advancing intelligent packaging business. The perspective that is attained through the research questions demonstrates the potential customer companies’ views of possibilities and problems. The key results suggest that intellectual property of relevant products is in an important position from the customers’ perspective. If the supplier does not own a product technology, a sufficiently large company can consider working as an integrator in a network where smaller companies make use of a compiled offering from other smaller actors. The foundation for these networks and company relationships is value creation, which has to be based on profound customer knowledge and research. The framework that is created for this study builds upon earlier research to provide a model that better serves intelligent packaging implementation and includes the notion of importance of value proposition and continuous value co-creation.

Sähkön siirtohinnat Suomessa 2015

Tässä kandidaatintyössä selvitetään kirjallisuustutkimuksena sähkön yleissiirtohinnat Suomessa vuonna 2015. Työssä vertaillaan sähkön siirtohintoja erilaisilla kotitalouskuluttajilla ja tutkitaan sähkönsiirron hinnoitteluun vaikuttavia tekijöitä. Työssä esitetään myös tulevaisuudessa mahdollisesti käytettäviä siirtotariffeja. Työ tuo esiin sähkön siirtohinnan komponenttien osuudet sähkönsiirron kokonaishinnasta, sekä havainnollistaa visuaalisesti komponenttien maantieteellistä vaihtelua. Siirtomaksujen vaihtelua erilaisilla kulutuksilla havainnollistetaan käyttämällä kolmea esimerkkikuluttajaa, sekä vertailemalla esimerkkikuluttajien siirtomaksuja keskenään. Siirtomaksujen kokonaiskustannusten maantieteellistä vaihtelua havainnollistetaan kuvien avulla. Energiaviraston regulaation vaikutuksia siirtohintaan tarkastellaan verkkoyhtiöiden yli- ja alijäämien avulla. Tulevaisuuden siirtotariffeista huomio kiinnittyy kaistahinnoitteluun. Kaistahinnoittelua tarkastellaan kuluttajan kannalta ja samalla tuodaan esiin kaistahinnoittelun etuja nykyisin käytössä oleviin siirtotariffeihin. Työn perusteella voidaan tehdä johtopäätös, että sähkön kulutuksen kasvaessa siirtomaksu kulutettua energiayksikköä kohden pienenee. Toisin sanoen perusmaksun osuus on merkittävä pienillä kulutusmäärillä ja sen suhteellinen osuus siirtomaksuista pienenee kulutuksen kasvaessa.

Performance improvement in mediterranean operations using risk management analysis : Case study of Containerships Group Ltd

Emerging markets of Northern Africa and Turkey provide growth opportunities for logistics service companies in the middle of low growth environment of European Union. The purpose of this research is to explore and analyze the risk factors in container shipping industry and third party logistics (3PL) services. The research empirically examined the risk factors, which are related within the interaction between these two parties in emerging markets of Mediterranean area. The previous studies have provided a valuable insight into the operational risks faced by container shipping industries. However, most of these studies have focused on one or several operational risk factors from a single point of view, and no studies have inclusively examined the possible operational risks faced in the container shipping industry from dual perspective of 3PL provider and its customers. A questionnaire has been deployed to collect related data; and the impacts of the risks were then be assessed and ranked using the method of risk mapping. Respondents were located in Turkey, Algeria, Tunisia, and Libya. Research presents the most important risk factors identified, and compares them between 3PL provider and its customers. The research also provide some risk mitigation strategies for the key risk factors, and tried to figure out a common risk picture, which guides the managers in both sides to have a better decisions and as a result, improve the performance of the container shipping operations. Challenge during project execution time was that customers identified vast amount of more risks than what was the case with logistics service operator.

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.

Evaluation of the main energy scenarios for the global energy transition

Energy scenarios are used as a tool to examine credible future states and pathways. The one who constructs a scenario defines the framework in which the possible outcomes exist. The credibility of a scenario depends on its compatibility with real world experiences, and on how well the general information of the study, methodology, and originality and processing of data are disclosed. In the thesis, selected global energy scenarios’ transparency and desirability from the society’s point of view were evaluated based on literature derived criteria. The global energy transition consists of changes to social conventions and economic development in addition to technological development. Energy solutions are economic and ethical choices due to far-reaching impacts of energy decision-making. Currently the global energy system is mostly based on fossil fuels, which is unsustainable over the long-term due to various reasons: negative climate change impacts, negative health impacts, depletion of fossil fuel reserves, resource-use conflicts with water management and food supply, loss of biodiversity, challenge to preserve ecosystems and resources for future generations, and inability of fossil fuels to provide universal access to modern energy services. Nuclear power and carbon capture and storage cannot be regarded as sustainable energy solutions due to their inherent risks and required long-term storage. The energy transition is driven by a growing energy demand, decreasing costs of renewables, modularity and scalability of renewable technologies, macroeconomic benefits of using renewables, investors’ risk awareness, renewable energy related attractive business opportunities, almost even distribution of solar and wind resources on the planet, growing awareness of the planet’s environmental status, environmental movements and tougher environmental legislation. Many of the investigated scenarios identified solar and wind power as a backbone for future energy systems. The scenarios, in which the solar and wind potentials were deployed in largest scale, met best the set out sustainability criteria. In future research, energy scenarios’ transparency can be improved by better disclosure on who has ordered the study, clarifying the funding, clearly referencing to used sources and indicating processed data, and by exploring how variations in cost assumptions and deployment of technologies influence on the outcomes of the study.