Трансфер технологий из Финляндии в советскую лесную промышленность в 1953 – 1964 гг.
The paper deals with transfer of Western technologies into the Soviet forestry concentrating on the area of Karelian Peninsula and Ladoga Karelia in 1953 - 1964. The area was a center in the Nikita Khrushchev`s modernization as there were several large factories which produced pulp and paper. Specialists from the factories were sent to Finland within the Soviet-Finnish cooperation to study Western technologies. In this I examine their activities as well as technologies they brought to the Soviet-Union.
The paper deals with transfer of Western technologies into the Soviet forestry within the Soviet-Finnish cooperation in 1953-1964. It is focused on the area of Karelian Peninsula and Ladoga Karelia which was an emphasis in Khrushchev`s modernization of the forestry sector.Specialists from the factories of the area were sent to Finland within the Soviet-Finnish cooperation to study Western technologies while Finnish specialists came to the Soviet Union to share their experience. In this paper I examine their activities to bring technologies to the Soviet-Union
One of the most important key factors for the development of non-urban areas is infrastructure, and energy generation is one of the fundamental infrastructure elements. This paper provides a new solution for energy generation based on wood chips which has a multi-sector effect because the authors offer to combine planning of forest cleaning cutting with bioenergy generation in one complex project, which will have socio-economic and ecological effects. The situation with forest fires makes the authors’ idea more attractive because after forest fires the problem of cleaning cutting in forest becomes very important and urgent by ecological and economical points: after cleaning cutting there are a lot of low quality wood which can be recycled into chips for the production bioenergy by the authors’ idea. This enriched methodology has successfully been applied into the regional strategical planning in the field of bioenergy and forestry of the Ural region of Russia; however, it is suitable for applications in regional development in any non-urban forested region of the world.
The study includes a variety of topics, from a review of the political, legal and institutional frameworks for the development of a “green economy” in Russia, to concrete practices of separate waste collection, the development of renewable energy sources and aspects of environmental education. We tried to look at the process of sustainable development in Russia from diff erent perspectives, including the political and economic background, the legal situation, existing practices of sustainable development and how environmental information circulated, including journalism and education on sustainable development. The result is a broad study, which includes a collection of articles written by both theorists and practitioners of sustainable development in Russia.
Distinguishing outliers from normal data in wireless sensor networks has been a big challenge in the anomaly detection domain, mostly due to the nature of the anomalies, such as software or hardware failures, reading errors or malicious attacks, just to name a few. In this article, we introduce an anomaly detection-based OPF classifier in the aforementioned context. The results are compared against one-class support vector machines and multivariate Gaussian distribution. Additionally, we also propose to employ meta-heuristic optimization techniques to finetune the OPF classifier in the context of anomaly detection in wireless sensor networks.